Research Track Papers

Research Track Papers Schedule

SESSION 1

Tuesday, August 8, 10:00 AM-12:00 PM, Room 102C, (Anomaly Detection). Session Chair: Latifur Khan

Anomaly Detection with Score Distribution Discrimination

Minqi Jiang (Shanghai University of Finance and Economics), Songqiao Han (Shanghai University of Finance and Economics), Hailiang Huang (Shanghai University of Finance and Economics)

Data-Efficient and Interpretable Tabular Anomaly Detection

Chun-Hao Chang (Meta), Jinsung Yoon (Google Cloud AI), Sercan Arik (Google Cloud AI), Madeleine Udell (Stanford University), Tomas Pfister (Google Cloud AI)

DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection

Yiyuan Yang (University of Oxford), Chaoli Zhang (Alibaba Group), Tian Zhou (Alibaba Group), Qingsong Wen (Alibaba Group), Liang Sun (Alibaba Group)

Deep Weakly-Supervised Anomaly Detection

Guansong Pang (Singapore Management University), Chunhua Shen (Zhejiang University), Huidong Jin (Data61), Anton van den Hengel (University of Adelaide)

Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection

Lorenzo Perini (KU Leuven), Vincent Vercruyssen (KU Leuven), Jesse Davis (KU Leuven)

Precursor-of-Anomaly Detection for Irregular Time Series

Sheo yon Jhin (Yonsei University), Jaehoon Lee (LG AI Research; Yonsei University), Noseong Park (Yonsei University)

Tuesday, August 8, 10:00 AM-12:00 PM, Room 103A, (NLP I). Session Chair: Kaize Ding

MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer

Yazheng Yang (The University of Hong Kong), Zhou Zhao (Zhejiang University), Qi Liu (The University of Hong Kong)

CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning

Jianfeng He (Virginia Tech), Xuchao Zhang (Microsoft), Shuo Lei (Virginia Tech), Abdulaziz Alhamadani (Virginia Tech), Fanglan Chen (Virginia Tech), Bei Xiao (American University), Chang-Tien Lu (Virginia Tech)

MetricPrompt: Prompting Model as a Relevance Metric for Few-Shot Text Classification

Hongyuan Dong (Harbin Institute of Technology), Weinan Zhang (Harbin Institute of Technology), Wanxiang Che (Harbin Institute of Technology)

Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler

Zhijun Chen (Beihang University), Hailong Sun (Beihang University), Wanhao Zhang (Tsinghua University), Chunyi Xu (Beihang University), Qianren Mao (Zhongguancun Laboratory), Pengpeng Chen (China’s Aviation System Engineering Research Institute)

A Sequence-to-Sequence Approach with Mixed Pointers to Topic Segmentation and Segment Labeling

Jinxiong Xia (Peking University), Houfeng Wang (Peking University)

Open-Set Semi-Supervised Text Classification with Latent Outlier Softening

Junfan Chen (Beihang University), Richong Zhang (Beihang University), Junchi Chen (Beihang University), Chunming Hu (Beihang University), Yongyi Mao (University of Ottawa)

Tuesday, August 8, 10:00 AM-12:00 PM, Room 103B, (Efficient ML). Session Chair: Yuxiao Dong

Constraint-Aware and Ranking-Distilled Token Pruning for Efficient Transformer Inference

Junyan Li (Zhejiang University), Li Lyna Zhang (Microsoft Research), Jiahang Xu (Microsoft Research), Yujing Wang (Microsoft), Shaoguang Yan (Microsoft), Yunqing Xia (Microsoft), Yuqing Yang (Microsoft Research), Ting Cao (Microsoft Research), Hao Sun (Microsoft), Weiwei Deng (Microsoft), Qi Zhang (Microsoft), Mao Yang (Microsoft Research)

COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search

Shibal Ibrahim (Massachusetts Institute of Technology), Wenyu Chen (Massachusetts Institute of Technology), Hussein Hazimeh (Google Research), Natalia Ponomareva (Google Research), Zhe Zhao (Google DeepMind), Rahul Mazumder (Massachusetts Institute of Technology)

Kernel Ridge Regression-Based Graph Dataset Distillation

Zhe Xu (University of Illinois Urbana-Champaign), Yuzhong Chen (Visa Research), Menghai Pan (Visa Research), Huiyuan Chen (Visa Research), Mahashweta Das (Visa Research), Hao Yang (Visa Research), Hanghang Tong (University of Illinois Urbana-Champaign)

Efficient Coreset Selection with Cluster-Based Methods

Chengliang Chai (Beijing Institute of Technology), Jiayi Wang (Tsinghua University), Nan Tang (HKUST(GZ)), Ye Yuan (Beijing Institute of Technology), Jiabin Liu (Beijing Institute of Technology), Yuhao Deng (Beijing Institute of Technology), Guoren Wang (Beijing Institute of Technology)

The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles

Md Shamim Hussain (Rensselaer Polytechnic Institute), Mohammed J. Zaki (Rensselaer Polytechnic Institute), Dharmashankar Subramanian (International Business Machines)

Tuesday, August 8, 10:00 AM-12:00 PM, Room 103C, (Ranking). Session Chair: Ruocheng Guo

Off-Policy Evaluation of Ranking Policies under Diverse User Behavior

Haruka Kiyohara (Hanjuku-Kaso Co., Ltd.), Masatoshi Uehara (Cornell University), Yusuke Narita (Yale University), Nobuyuki Shimizu (Yahoo Japan Corporation), Yasuo Yamamoto (Yahoo Japan Corporation), Yuta Saito (Cornell University)

Generative Flow Network for Listwise Recommendation

Shuchang Liu (Kuaishou Technology), Qingpeng Cai (Kuaishou Technology), Zhankui He (University of California, San Diego), Sun Bowen (Peking University), Julian McAuley (University of California, San Diego), Dong Zheng (Kuaishou Technology), Peng Jiang (Kuaishou Technology), Kun Gai (Unaffiliated)

Rank-heterogeneous Preference Models for School Choice

Amel Awadelkarim (Stanford University), Arjun Seshadri (Amazon), Itai Ashlagi (Stanford University), Irene Lo (Stanford University), Johan Ugander (Stanford University)

Querywise Fair Learning to Rank through Multi-Objective Optimization

Debabrata Mahapatra (National University of Singapore), Chaosheng Dong (Amazon), Michinari Momma (Amazon)

PSLOG: Pretraining with Search Logs for Document Ranking

Zhan Su (Renmin University of China), Zhicheng Dou (Renmin University of China), Yujia Zhou (Renmin University of China), Ziyuan Zhao (Tencent), Ji-Rong Wen (Engineering Research Center of Next-Generation Intelligent Search and Recommendation, Ministry of Education; Renmin University of China)

Tuesday, August 8, 10:00 AM-12:00 PM, Room 201A, (Graph Mining I). Session Chair: Matteo Riondato

Reducing Exposure to Harmful Content via Graph Rewiring

Corinna Coupette (Max Planck Institute for Informatics), Stefan Neumann (KTH Royal Institute of Technology), Aristides Gionis (KTH Royal Institute of Technology)

Efficient Approximation Algorithms for Spanning Centrality

Shiqi Zhang (National University of Singapore; Southern University of Science and Technology), Renchi Yang (Hong Kong Baptist University), Jing Tang (The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology), Xiaokui Xiao (National University of Singapore), Bo Tang (Southern University of Science and Technology)

A Higher-Order Temporal H-Index for Evolving Networks

Lutz Oettershagen (KTH Royal Institute of Technology), Nils M. Kriege (University of Vienna), Petra Mutzel (University of Bonn)

Quantifying Node Importance over Network Structural Stability

Fan Zhang (Guangzhou University), Qingyuan Linghu (University of New South Wales), Jiadong Xie (Chinese University of Hong Kong), Kai Wang (Shanghai Jiao Tong University), Xuemin Lin (Shanghai Jiao Tong University), Wenjie Zhang (University of New South Wales)

Efficient Centrality Maximization with Rademacher Averages

Leonardo Pellegrina (University of Padova)

Accelerating Personalized PageRank Vector Computation

Zhen Chen (Fudan University), Xingzhi Guo (State University of New York at Stony Brook), Baojian Zhou (Fudan University), Deqing Yang (Fudan University), Steven Skiena (State University of New York at Stony Brook)

Tuesday, August 8, 10:00 AM-12:00 PM, Room 201B, (Social Computing). Session Chair: Tim Weninger

Community-based Dynamic Graph Learning for Popularity Prediction

Shuo Ji (Beihang University), Xiaodong Lu (Beihang University), Mingzhe Liu (Beihang University), Leilei Sun (Beihang University), Chuanren Liu (The University of Tennessee), Bowen Du (Beihang University), Hui Xiong (The Hong Kong University of Science and Technology)

Fair Allocation Over Time, with Applications to Content Moderation

Amine Allouah (Meta), Christian Kroer (Columbia University), Xuan Zhang (Meta), Vashist Avadhanula (Meta), Nona Bohanon (Meta), Anil Dania (Meta), Caner Gocmen (Meta), Sergey Pupyrev (Meta), Parikshit Shah (Meta), Nicolas Stier-Moses (Meta), Ken Rodriguez Taarup (Meta)

A Sublinear Time Algorithm for Opinion Optimization in Directed Social Networks via Edge Recommendation

Xiaotian Zhou (Fudan University), Liwang Zhu (Fudan University), Wei Li (Fudan University), Zhongzhi Zhang (Fudan University)

Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting

Christine Herlihy (University of Maryland), Aviva Prins (University of Maryland), Aravind Srinivasan (University of Maryland), John P. Dickerson (University of Maryland)

How Transitive Are Real-World Group Interactions? Measurement and Reproduction

Sunwoo Kim (KAIST), Fanchen Bu (KAIST), Minyoung Choe (KAIST), Jaemin Yoo (Carnegie Mellon University), Kijung Shin (KAIST)

Predicting Information Pathways Across Online Communities

Yiqiao Jin (Georgia Institute of Technology), Yeon-Chang Lee (Georgia Institute of Technology), Kartik Sharma (Georgia Institute of Technology), Meng Ye (SRI International), Karan Sikka (SRI International), Ajay Divakaran (SRI International), Srijan Kumar (Georgia Institute of Technology)

SESSION 2

Tuesday, August 8, 1:30 PM-3:30 PM, Room 102C, (AutoML). Session Chair: Slawomir Nowaczyk

Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data

Yaoqing Yang (Dartmouth College), Ryan Theisen (University of California Berkeley), Liam Hodgkinson (University of Melbourne), Joseph E. Gonzalez (University of California, Berkeley), Kannan Ramchandran (University of California Berkeley), Charles H. Martin (Calculation Consulting), Michael W. Mahoney (University of California Berkeley)

Deep Pipeline Embeddings for AutoML

Sebastian Pineda Arango (University of Freiburg), Josif Grabocka (University of Freiburg)

Dependence and Model Selection in LLP: The Problem of Variants

Gabriel Franco (Boston University), Mark Crovella (Boston University), Giovanni Comarela (Federal University of Espírito Santo)

Rapid Image Labeling via Neuro-Symbolic Learning

Yifeng Wang (The Hong Kong Polytechnic University), Zhi Tu (Purdue University), Yiwen Xiang (Chongqing University), Shiyuan Zhou (University of Toronto), Xiyuan Chen (University of Toronto), Bingxuan Li (Purdue University), Tianyi Zhang (Purdue University)

Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering

Yan Wen (Tsinghua University), Chen Gao (Tsinghua University), Lingling Yi (Tencent Inc.), Liwei Qiu (Tencent Inc.), Yaqing Wang (Baidu Inc.), Yong Li (Tsinghua University)

Tuesday, August 8, 1:30 PM-3:30 PM, Room 103A, (NLP II). Session Chair: Qi Li

CFGL-LCR: A Counterfactual Graph Learning framework for Legal Case Retrieval

Kun Zhang (Institute of Computing Technology, Chinese Academy of Sciences), Chong Chen (Huawei Cloud BU.), Yuanzhuo Wang (Institute of Computing Technology, Chinese Academy of Sciences), Qi Tian (Huawei Cloud BU.), Long Bai (Institute of Computing Technology, Chinese Academy of Sciences)

Dense Representation Learning and Retrieval for Tabular Data Prediction

Lei Zheng (Shanghai Jiao Tong University), Ning Li (Shanghai Jiao Tong University), Xianyu Chen (Shanghai Jiao Tong University), Quan Gan (Shanghai Jiao Tong University), Weinan Zhang (Shanghai Jiao Tong University)

LEA: Improving Sentence Similarity Robustness to Typos Using Lexical Attention Bias

Mario Almagro (NielsenIQ Innovation), Emilio Almazán (NielsenIQ Innovation), Diego Ortego (NielsenIQ Innovation), David Jiménez (NielsenIQ Innovation)

LightToken: A Task and Model-Agnostic Lightweight Token Embedding Framework for Pre-trained Language Models

Haoyu Wang (Purdue University), Ruirui Li (Amazon.com Inc), Haoming Jiang (Amazon.com Inc), Zhengyang Wang (Amazon.com Inc), Xianfeng Tang (Amazon.com Inc), Bin Bi (Amazon.com Inc), Monica Cheng (Amazon.com Inc), Bing Yin (Amazon.com Inc), Yaqing Wang (Purdue University), Tuo Zhao (Georgia Institute of Technology), Jing Gao (Purdue University)

DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling

Yuchen Zhuang (Georgia Institute of Technology), Yue Yu (Georgia Institute of Technology), Lingkai Kong (Georgia Institute of Technology), Xiang Chen (Adobe Research), Chao Zhang (Georgia Institute of Technology)

GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network

Ran Jia (Microsoft), Haoming Guo (University of California, Berkeley), Xiaoyuan Jin (ETH ZÈªµich), Chao Yan (Peking University), Lun Du (Microsoft), Xiaojun Ma (Microsoft), Tamara Stankovic (Microsoft), Marko Lozajic (Microsoft), Goran Zoranovic (Microsoft), Igor Ilic (Microsoft), Shi Han (Microsoft), Dongmei Zhang (Microsoft)

Tuesday, August 8, 1:30 PM-3:30 PM, Room 103B, (Explainable AI). Session Chair: Xiangliang Zhang

Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective

Jihong Wang (Xi’an Jiaotong University), Minnan Luo (Xi’an Jiaotong University), Jundong Li (University of Virginia), Yun Lin (Shanghai Jiao Tong University), Yushun Dong (University of Virginia), Jin Song Dong (National University of Singapore), Qinghua Zheng (Xi’an Jiaotong University)

MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation

Jiaxing Zhang (New Jersey Institute of Technology), Dongsheng Luo (Florida International University), Hua Wei (NJIT; Arizona State University)

CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations

Hangzhi Guo (Pennsylvania State University), Thanh Hong Nguyen (Pennsylvania State University), Amulya Yadav (Pennsylvania State University)

Fire: An Optimization Approach for Fast Interpretable Rule Extraction

Brian Liu (Massachusetts Institute of Technology), Rahul Mazumder (Massachusetts Institute of Technology)

ESSA: Explanation Iterative Supervision via Saliency-Guided Data Augmentation

Siyi Gu (Emory University), Yifei Zhang (Emory University), Yuyang Gao (Home Depot), Xiaofeng Yang (Emory University), Liang Zhao (Emory University)

A Causality Inspired Framework for Model Interpretation

Chenwang Wu (University of Science and Technology of China), Xiting Wang (University of Science and Technology of China), Defu Lian (University of Science and Technology of China), Xing Xie (University of Science and Technology of China), Enhong Chen (University of Science and Technology of China)

Tuesday, August 8, 1:30 PM-3:30 PM, Room 103C, (Graph Representation Learning). Session Chair: Lei Li

Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-Scale Disentangled Representations

Haoyu Geng (Shanghai Jiao Tong University), Chao Chen (Shanghai Jiao Tong University), Yixuan He (University of Oxford), Gang Zeng (Didi Chuxing), Zhaobing Han (Didi Chuxing), Hua Chai (Didi Chuxing), Junchi Yan (Shanghai Jiao Tong University)

What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

Jintang Li (Sun Yat-sen University), Ruofan Wu (Ant Group), Wangbin Sun (Sun Yat-sen University), Liang Chen (Sun Yat-sen University), Sheng Tian (Ant Group), Liang Zhu (Ant Group), Changhua Meng (Ant Group), Zibin Zheng (Sun Yat-sen University), Weiqiang Wang (Ant Group)

Efficient and Effective Edge-Wise Graph Representation Learning

Hewen Wang (National University of Singapore), Renchi Yang (Hong Kong Baptist University), Keke Huang (National University of Singapore), Xiaokui Xiao (National University of Singapore)

Towards Graph-Level Anomaly Detection via Deep Evolutionary Mapping

Xiaoxiao Ma (Macquarie University), Jia Wu (Macquarie University), Jian Yang (Macquarie University), Quan Z. Sheng (Macquarie University)

VQNE: Variational Quantum Network Embedding with Application to Network Alignment

Xinyu Ye (Shanghai Jiao Tong University), Ge Yan (Shanghai Jiao Tong University), Junchi Yan (Shanghai Jiao Tong University)

CARL-G: Clustering-Accelerated Representation Learning on Graphs

William Shiao (University of California, Riverside), Uday Singh Saini (University of California, Riverside), Yozen Liu (Snap Inc.), Tong Zhao (Snap Inc.), Neil Shah (Snap Inc.), Evangelos E. Papalexakis (University of California, Riverside)

Tuesday, August 8, 1:30 PM-3:30 PM, Room 201A, (Graph Mining II). Session Chair: Yifeng Gao

Optimal Dynamic Subset Sampling: Theory and Applications

Lu Yi (Renmin University of China), Hanzhi Wang (Renmin University of China), Zhewei Wei (Renmin University of China)

Capacity Constrained Influence Maximization in Social Networks

Shiqi Zhang (National University of Singapore; Southern University of Science and Technology), Yiqian Huang (Southern University of Science and Technology), Jiachen Sun (Tencent), Wenqing Lin (Tencent), Xiaokui Xiao (National University of Singapore), Bo Tang (Southern University of Science and Technology)

On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms

Fanchen Bu (KAIST), Kijung Shin (KAIST)

Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity

Atsushi Miyauchi (CENTAI Institute), Tianyi Chen (Boston University), Konstantinos Sotiropoulos (Boston University), Charalampos E. Tsourakakis (Boston University)

Minimizing Hitting Time between Disparate Groups with Shortcut Edges

Florian Adriaens (University of Helsinki), Honglian Wang (KTH Royal Institute of Technology), Aristides Gionis (KTH Royal Institute of Technology)

Sequential Learning Algorithms for Contextual Model-Free Influence Maximization

Alexandra Iacob (Universit Paris-Saclay), Bogdan Cautis (Universit Paris-Saclay), Silviu Maniu (Universit Paris-Saclay)

Tuesday, August 8, 1:30 PM-3:30 PM, Room 201B, (Spatiotemporal Data). Session Chair: Zhe Jiang

Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning

Zhengyang Zhou (University of Science and Technology of China), Qihe Huang (University of Science and Technology of China), Kuo Yang (University of Science and Technology of China), Kun Wang (University of Science and Technology of China), Xu Wang (University of Science and Technology of China), Yudong Zhang (University of Science and Technology of China), Yuxuan Liang (University of Science and Technology of China), Yang Wang (University of Science and Technology of China)

Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning

Xin Qin (Beijing Key Lab. of Mobile Com., CAS), Jindong Wang (Microsoft Research Asia), Shuo Ma (Beijing Key Lab. of Mobile Com., CAS), Wang Lu (Beijing Key Lab. of Mobile Com., CAS), Yongchun Zhu (Beijing Key Lab. of Mobile Com., CAS), Xin Xie (Microsoft Research Asia), Yiqiang Chen (Beijing Key Lab. of Mobile Com., CAS)

Localised Adaptive Spatial-Temporal Graph Neural Network

Wenying Duan (Nanchang University), Xiaoxi He (University of Macau), Zimu Zhou (City University of Hong Kong), Lothar Thiele (ETH Zurich), Hong Rao (Nanchang University)

Spatio-Temporal Diffusion Point Processes

Yuan Yuan (Department of Electronic Engineering, Tsinghua University), Jingtao Ding (Department of Electronic Engineering, Tsinghua University), Chenyang Shao (Department of Electronic Engineering, Tsinghua University), Depeng Jin (Department of Electronic Engineering, Tsinghua University), Yong Li (Department of Electronic Engineering, Tsinghua University)

ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSM

Mingzhi Hu (Worcester Polytechnic Institute), Xin Zhang (Worcester Polytechnic Institute), Yanhua Li (Worcester Polytechnic Institute), Xun Zhou (University of Iowa), Jun Luo (Lenovo Group Limited)

On Hierarchical Disentanglement of Interactive Behaviors for Multimodal Spatiotemporal Data with Incompleteness

Jiayi Chen (University of Virginia), Aidong Zhang (University of Virginia)

Tuesday, August 8, 1:30 PM-3:30 PM, Room 104C, (Weakly-Supervised Learning). Session Chair: Zhuangdi Zhu

Complementary Classifier Induced Partial Label Learning

Yuheng Jia (Southeast University), Chongjie Si (Shanghai Jiao Tong University), Min-Ling Zhang (Southeast University)

Deep Encoders with Auxiliary Parameters for Extreme Classification

Kunal Dahiya (IIT Delhi), Sachin Yadav (Microsoft Research), Sushant Sondhi (IIT Delhi), Deepak Saini (Microsoft), Sonu Mehta (Microsoft Research; IIT Delhi), Jian Jiao (Microsoft), Sumeet Agarwal (IIT Delhi), Purushottam Kar (IIT Kanpur), Manik Varma (Microsoft Research)

Semantic Dissimilarity Guided Locality Preserving Projections for Partial Label Dimensionality Reduction

Yuheng Jia (Southeast University), Jiahao Jiang (Southeast University), Yongheng Wang (Zhejiang Lab)

To Aggregate or Not? Learning with Separate Noisy Labels

Jiaheng Wei (University of California, Santa Cruz), Zhaowei Zhu (University of California, Santa Cruz), Tianyi Luo (Amazon Search Science and AI), Ehsan Amid (Google Research, Brain Team), Abhishek Kumar (University of California, Santa Cruz), Yang Liu (University of California, Santa Cruz)

Partial-label Learning with Mixed Closed-Set and Open-Set Out-of-Candidate Examples

Shuo He (University of Electronic Science and Technology of China), Lei Feng (Nanyang Technological University), Guowu Yang (University of Electronic Science and Technology of China)

Local Boosting for Weakly-Supervised Learning

Rongzhi Zhang (Georgia Institute of Technology), Yue Yu (Georgia Institute of Technology), Jiaming Shen (Georgia Institute of Technology), Xiquan Cui (Georgia Institute of Technology), Chao Zhang (Georgia Institute of Technology)

SESSION 3

Tuesday, August 8, 4:00 PM-6:00 PM, Room 101B, (ML for System). Session Chair: Xia “Ben” Hu

One for All: Unified Workload Prediction for Dynamic Multi-Tenant Edge Cloud Platforms

Shaoyuan Huang (Tianjin University), Zheng Wang (Tianjin University), Heng Zhang (Tianjin University), Xiaofei Wang (Tianjin University), Cheng Zhang (Tianjin University of Finance; Economics), Wenyu Wang (Paiou Cloud Computing (Shanghai) Co., Ltd)

GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction

Haoyu Geng (Shanghai Jiao Tong University), Runzhong Wang (Shanghai Jiao Tong University), Fei Wu (Zhejiang University), Junchi Yan (Shanghai Jiao Tong University)

Learning Autoregressive Model in LSM-Tree based Store

Yunxiang Su (Tsinghua University), Wenxuan Ma (Tsinghua University), Shaoxu Song (Tsinghua University)

PERT-GNN: Latency Prediction for Microservice-Based Cloud-Native Applications via Graph Neural Networks

Da Sun Handason Tam (The Chinese University of Hong Kong), Yang Liu (Shanghai University), Huanle Xu (University of Macau), Siyue Xie (The Chinese University of Hong Kong), Wing Cheong Lau (The Chinese University of Hong Kong)

IPOC: An Adaptive Interval Prediction Model based on Online Chasing and Conformal Inference for Large-Scale Systems

Jiadong Chen (Shanghai Jiao Tong University), Yang Luo (Shanghai Jiao Tong University), Xiuqi Huang (Shanghai Jiao Tong University), Fuxin Jiang (Bytedance Inc.), Yangguang Shi (Shandong University), Tieying Zhang (Bytedance Inc.), Xiaofeng Gao (Shanghai Jiao Tong University)

A Dual-Agent Scheduler for Distributed Deep Learning Jobs on Public Cloud via Reinforcement Learning

Mingzhe Xing (Peking University), Hangyu Mao (Sensetime Research), Shenglin Yin (Peking University), Lichen Pan (Peking University), Zhengchao Zhang (ByteDance), Zhen Xiao (Peking University), Jieyi Long (Theta Labs, Inc.)

Tuesday, August 8, 4:00 PM-6:00 PM, Room 102C, (Causal Inference). Session Chair: Changlin Wan

Treatment Effect Estimation with Adjustment Feature Selection

Haotian Wang (National University of Defense Technology), Kun Kuang (Zhejiang University), Haoang Chi (Defense Innovation Institute), Longqi Yang (Defense Innovation Institute), Mingyang Geng (National University of Defense Technology), Wanrong Huang (National University of Defense Technology), Wenjing Yang (National University of Defense Technology)

Specify Robust Causal Representation from Mixed Observations

Mengyue Yang (University College London), Xinyu Cai (Nanyang Technological University), Furui Liu (Zhejiang Lab), Weinan Zhang (Shanghai Jiao Tong University), Jun Wang (University College London)

CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems

Song Jiang (University of California, Los Angeles), Zijie Huang (University of California, Los Angeles), Xiao Luo (University of California, Los Angeles), Yizhou Sun (University of California, Los Angeles)

Detecting Interference in Online Controlled Experiments with Increasing Allocation

Kevin Han (Stanford University), Shuangning Li (Harvard University), Jialiang Mao (LinkedIn Corporation), Han Wu (Stanford University)

Causal Effect Estimation on Hierarchical Spatial Graph Data

Koh Takeuchi (Kyoto University), Ryo Nishida (AIST), Hisashi Kashima (Kyoto University), Masaki Onishi (AIST)

Tuesday, August 8, 4:00 PM-6:00 PM, Room 103A, (Optimization). Session Chair: Yaoqing Yang

Communication Efficient Distributed Newton Method with Fast Convergence Rates

Chengchang Liu (The Chinese University of Hong Kong), Lesi Chen (Fudan University), Luo Luo (Fudan University), John Lui (Chinese University of Hong Kong)

Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint

Wei Liu (School of Computer Science and Technology, Huazhong University of Science and Technology), Jun Wang (iWudao.tech), Haozhao Wang (School of Computer Science and Technology, Huazhong University of Science and Technology), Ruixuan Li (School of Computer Science and Technology, Huazhong University of Science and Technology), Yang Qiu (School of Computer Science and Technology, Huazhong University of Science and Technology), YuanKai Zhang (School of Computer Science and Technology, Huazhong University of Science and Technology), Jie Han (School of Computer Science and Technology, Huazhong University of Science and Technology), Yixiong Zou (School of Computer Science and Technology, Huazhong University of Science and Technology)

Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term

Yun Yue (Ant Group), Jiadi Jiang (Ant Group), Zhiling Ye (Ant Group), Ning Gao (Ant Group), Yongchao Liu (Ant Group), Ke Zhang (Ant Group)

Fragility Index: A New Approach for Binary Classification

Chen Yang (Hong Kong University of Science and Technology), Ziqiang Zhang (Alibaba Group), Bo Cao (Alibaba Group), Zheng Cui (Zhejiang University), Bin Hu (CITIC Securities), Tong Li (Alibaba Group), Daniel Zhuoyu Long (The Chinese University of Hong Kong), Jin Qi (Hong Kong University of Science and Technology), Feng Wang (Alibaba Group), Ruohan Zhan (Hong Kong University of Science and Technology)

Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time

Yixin Chen (Texas AM University), Alan Kuhnle (Texas AM University)

Efficient Sparse Linear Bandits under High Dimensional Data

Xue Wang ( Alibaba Group US), Mike Mingcheng Wei (University at Buffalo), Tao Yao (The Chinese University of Hong Kong, Shenzhen)

Tuesday, August 8, 4:00 PM-6:00 PM, Room 103B, (Expressiveness of Graph Neural Network). Session Chair: Yanfang Ye

Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information

Tianjun Yao (Mohamed bin Zayed University of Artificial Intelligence), Yingxu Wang (Mohamed bin Zayed University of Artificial Intelligence), Kun Zhang (Carnegie Mellon University), Shangsong Liang (Mohamed bin Zayed University of Artificial Intelligence)

A Message Passing Neural Network Space for Better Capturing Data-dependent Receptive Fields

Zhili Wang (HKUST), Shimin Di (HKUST), Lei Chen (HKUST (GZ); HKUST)

On Structural Expressive Power of Graph Transformers

Wenhao Zhu (Peking University), Tianyu Wen (Peking University), Guojie Song (Peking University), Liang Wang (Alibaba Group), Bo Zheng (Alibaba Group)

MGNN: Graph Neural Networks Inspired by Distance Geometry Problem

Guanyu Cui (Renmin University of China), Zhewei Wei (Renmin University of China)

Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization

Kaixuan Chen (Zhejiang University), Shunyu Liu (Zhejiang University), Tongtian Zhu (Zhejiang University), Ji Qiao (China Electric Power Research Institute), Yun Su (State Grid Shanghai Municipal Electric Power Company), Yingjie Tian (State Grid Shanghai Municipal Electric Power Company), Tongya Zheng (Zhejiang University), Haofei Zhang (Zhejiang University), Zunlei Feng (Zhejiang University), Jingwen Ye (Zhejiang University), Mingli Song (Zhejiang University)

Tuesday, August 8, 4:00 PM-6:00 PM, Room 103C, (Recommendation Systems). Session Chair: Bart Goethals

Text Is All You Need: Learning Language Representations for Sequential Recommendation

Jiacheng Li (University of California, San Diego), Ming Wang (Amazon), Jin Li (Amazon), Jinmiao Fu (Amazon), Xin Shen (Amazon), Jingbo Shang (University of California, San Diego), Julian McAuley (University of California, San Diego)

MAP: A Model-agnostic Pretraining Framework for Click-Through Rate Prediction

Jianghao Lin (Shanghai Jiao Tong University), Yanru Qu (Shanghai Jiao Tong University), Wei Guo (Huawei Noah’s Ark Lab), Xinyi Dai (Shanghai Jiao Tong University), Ruiming Tang (Huawei Noah’s Ark Lab), Yong Yu (Shanghai Jiao Tong University), Weinan Zhang (Shanghai Jiao Tong University)

Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction

Runlong Yu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Xiang Xu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Yuyang Ye (Rutgers University), Qi Liu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Enhong Chen (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence)

PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-Term User Engagement

Wanqi Xue (Nanyang Technological University), Qingpeng Cai (Kuaishou Technology), Zhenghai Xue (Nanyang Technological University), Shuo Sun (Nanyang Technological University), Shuchang Liu (Kuaishou Technology), Dong Zheng (Kuaishou Technology), Peng Jiang (Kuaishou Technology), Kun Gai (Unaffiliated), Bo An (Nanyang Technological University)

Efficient Bi-Level Optimization for Recommendation Denoising

Zongwei Wang (University of Chongqing), Min Gao (University of Chongqing), Wentao Li (The Hong Kong University of Science and Technology (Guangzhou)), Junliang Yu (University of Queensland), Linxin Guo (University of Chongqing), Hongzhi Yin (University of Queensland)

Adaptive Disentangled Transformer for Sequential Recommendation

Yipeng Zhang (Tsinghua University, Tsinghua University), Xin Wang (Tsinghua University, Tsinghua University), Hong Chen (Tsinghua University, Tsinghua University), Wenwu Zhu (Tsinghua University, Tsinghua University)

Tuesday, August 8, 4:00 PM-6:00 PM, Room 201A, (Graph Neural Networks). Session Chair: Hua Wei

Learning Strong Graph Neural Networks with Weak Information

Yixin Liu (Monash University), Kaize Ding (Arizona State University), Jianling Wang (Texas AM University), Vincent Lee (Monash University), Huan Liu (Arizona State University), Shirui Pan (Griffith University)

Clenshaw Graph Neural Networks

Yuhe Guo (Renmin University of China), Zhewei Wei (Renmin University of China)

All in One: Multi-Task Prompting for Graph Neural Networks

Xiangguo Sun (The Chinese University of Hong Kong), Hong Cheng (The Chinese University of Hong Kong), Jia Li (The Hong Kong University of Science and Technology (Guangzhou)), Bo Liu (Southeast University; Purple Mountain Laboratories), Jihong Guan (Tongji University)

Certified Edge Unlearning for Graph Neural Networks

Kun Wu (Stevens Institute of Technology), Jie Shen (Stevens Institute of Technology), Yue Ning (Stevens Institute of Technology), Ting Wang (Pennsylvania State University), Wendy Hui Wang (Stevens Institute of Technology)

Augmenting Recurrent Graph Neural Networks with a Cache

Guixiang Ma (Intel Labs), Vy A Vo (Intel Labs), Theodore L. Willke (Intel Labs), Nesreen K. Ahmed (Intel Labs)

Narrow the Input Mismatch in Deep Graph Neural Network Distillation

Qiqi Zhou (Hong Kong University of Science and Technology), Yanyan Shen (Shanghai Jiao Tong University), Lei Chen (Hong Kong University of Science and Technology; Hong Kong University of Science and Technology (Guangzhou))

Tuesday, August 8, 4:00 PM-6:00 PM, Room 201B, (Streaming Data). Session Chair: Abdullah Mueen

Finding Favourite Tuples on Data Streams with Provably Few Comparisons

Guangyi Zhang (Shenzhen Institute of Computing Sciences), Nikolaj Tatti (HIIT, University of Helsinki), Aristides Gionis (KTH Royal Institute of Technology)

SketchPolymer: Estimate Per-Item Tail Quantile Using One Sketch

Jiarui Guo (Peking University), Yisen Hong (Peking University), Yuhan Wu (Peking University), Yunfei Liu (Peking University), Tong Yang (Peking University), Bin Cui (Peking University)

Hyper-USS: Answering Subset Query Over Multi-Attribute Data Stream

Ruijie Miao (Peking University; Peng Cheng Laboratory), Yiyao Zhang (Nanjing University), Guanyu Qu (Institute of Computing Technology, Chinese Academy of Sciences; University of Chinese Academy of Sciences), Kaicheng Yang (Peking University; Peng Cheng Laboratory), Tong Yang (Peking University; Peng Cheng Laboratory), Bin Cui (Peking University)

Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors – Algorithm and Application

Jun-Gi Jang (Seoul National University), Jeongyoung Lee (Seoul National University), Yong-chan Park (Seoul National University), U Kang (Seoul National University)

MicroscopeSketch: Accurate Sliding Estimation Using Adaptive Zooming

Yuhan Wu (Peking University), Shiqi Jiang (Peking University), Siyuan Dong (Peking University), Zheng Zhong (Peking University), Jiale Chen (Peking University), Yutong Hu (Peking University), Tong Yang (Peking University), Steve Uhlig (Queen Mary University of London), Bin Cui (Peking University)

Sketch-Based Anomaly Detection in Streaming Graphs

Siddharth Bhatia (TurboML), Mohit Wadhwa (Google), Kenji Kawaguchi (National University of Singapore), Neil Shah (Snap Inc.), Philip Yu (University of Illinois at Chicago), Bryan Hooi (National University of Singapore)

SESSION 4

Wednesday, August 9, 10:00 AM-12:00 PM, Room 101B, (Knowledge and Reasoning II). Session Chair: Carl Yang

Guiding Mathematical Reasoning via Mastering Commonsense Formula Knowledge

Jiayu Liu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Zhenya Huang (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Zhiyuan Ma (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Qi Liu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Enhong Chen (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Tianhuang Su (OPPO Mobile Telecommunications), Haifeng Liu (University of Science and Technology of China)

Knowledge Graph Reasoning over Entities and Numerical Values

Jiaxin Bai (HKUST), Chen Luo (Amazon.com Inc), zheng li (Amazon.com Inc), Qingyu Yin (Amazon.com Inc), Bing Yin (Amazon.com Inc), Yangqiu Song (HKUST)

Exploiting Relation-Aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning

Gayeong Kim (Sungkyunkwan University), Sookyung Kim (Sungkyunkwan University), Ko Keun Kim (LG Electronics), Suchan Park (LG Electronics), Heesoo Jung (Sungkyunkwan University), Hogun Park (Sungkyunkwan University)

AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning

Yongqi Zhang (4Paradigm Inc.), Zhanke Zhou (Hong Kong Baptist University), Quanming Yao (Tsinghua University), Xiaowen Chu (HKUST (Guangzhou)), Bo Han (Hong Kong Baptist University)

Context-Aware Event Forecasting via Graph Disentanglement

Yunshan Ma (National University of Singapore), Chenchen Ye (National University of Singapore), Zijian Wu (National University of Singapore), Xiang Wang (University of Science and Technology of China), Yixin Cao (Singapore Management University), Tat-seng Chua (National University of Singapore)

Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers

Chanyoung Chung (KAIST), Jaejun Lee (KAIST), Joyce Jiyoung Whang (KAIST)

Wednesday, August 9, 10:00 AM-12:00 PM, Room 102C, (Causal Structure Learning). Session Chair: Dongjin Song

GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

Wentao Zhao (Shanghai Jiao Tong University), Qitian Wu (Shanghai Jiao Tong University), Chenxiao Yang (Shanghai Jiao Tong University), Junchi Yan (Shanghai Jiao Tong University)

Generative Causal Interpretation Model for Spatio-Temporal Representation Learning

Yu Zhao (Beihang University), Pan Deng (Beihang University), Junting Liu (Beihang University), Xiaofeng Jia (Beijing Big Data Centre), Jianwei Zhang (Capinfo Company Limited)

MM-DAG: Multi-task DAG Learning for Multi-Modal Data with Application for Traffic Congestion Analysis

Tian Lan (Tsinghua University), Ziyue Li (University of Cologne), zhishuai Li (SenseTime Research), Lei Bai (Shanghai AI Laboratory), Man Li (The Hong Kong University of Science and Technology), Fugee Tsung (The Hong Kong University of Science and Technology (Guangzhou)), Wolfgang Ketter (University of Cologne), Rui Zhao (SenseTime Research), Chen Zhang (Tsinghua University)

Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning

Deniz Koyuncu (Rensselaer Polytechnic Institute), Alex Gittens (Rensselaer Polytechnic Institute), Bluent Yener (Rensselaer Polytechnic Institute), Moti Yung (Google LLC; Columbia University)

Discovering Dynamic Causal Space for DAG Structure Learning

Fangfu Liu (Tsinghua University), Wenchang Ma (National University of Singapore), AN ZHANG (National University of Singapore), Xiang Wang (University of Science and Technology of China), Yueqi Duan (Tsinghua University), Tat-seng Chua (National University of Singapore)

Wednesday, August 9, 10:00 AM-12:00 PM, Room 103A, (Node Classification I). Session Chair: Ziniu Hu

Node Classification Beyond Homophily: Towards a General Solution

Zhe Xu (University of Illinois Urbana-Champaign), Yuzhong Chen (Visa Research), Qinghai Zhou (University of Illinois Urbana-Champaign), Yuhang Wu (Visa Research), Menghai Pan (Visa Research), Hao Yang (Visa Research), Hanghang Tong (University of Illinois Urbana-Champaign)

Grace: Graph Self-Distillation and Completion to Mitigate Degree-Relatednesses

Hui Xu (Shanghai Jiao Tong University), Liyao Xiang (Shanghai Jiao Tong University), Femke Huang (Shanghai Jiao Tong University), Yuting Weng (Shanghai Jiao Tong University), Ruijie Xu (Shanghai Jiao Tong University), Xinbing Wang (Shanghai Jiao Tong University), Chenghu Zhou (Chinese Academy of Sciences)

GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification

Wen-Zhi Li (Sun Yat-sen University; The Hong Kong University of Science and Technology (Guangzhou)), Chang-Dong Wang (Sun Yat-sen University), Hui Xiong (The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology), Jian-Huang Lai (Sun Yat-sen University)

Classification of Edge-Dependent Labels of Nodes in Hypergraphs

Minyoung Choe (Korea Advanced Institute of Science and Technology), Sunwoo Kim (Korea Advanced Institute of Science and Technology), Jaemin Yoo (Carnegie Mellon University), Kijung Shin (Korea Advanced Institute of Science and Technology)

Enhancing Graph Representations Learning with Decorrelated Propagation

Hua Liu (Shandong University), Wei Jin (Michigan State University), Xiaorui Liu (North Carolina State University), Hui Liu (Michigan State University)

HGCN: Tree-Likeness Modeling via Continuous and Discrete Curvature Learning

Menglin Yang (The Chinese University of Hong Kong), Min Zhou (Huawei Technologies Co., Ltd.), Lujia Pan (Huawei Technologies Co., Ltd.), Irwin King (The Chinese University of Hong Kong)

Wednesday, August 9, 10:00 AM-12:00 PM, Room 103B, (Fairness). Session Chair: Wei Ding

Path-Specific Counterfactual Fairness for Recommender Systems

Yaochen Zhu (University of Virginia), Jing Ma (University of Virginia), Liang Wu (LinkedIn Inc.), Qi Guo (LinkedIn Inc.), Liangjie Hong (LinkedIn Inc.), Jundong Li (University of Virginia)

SURE: Robust, Explainable, and Fair Classification without Sensitive Attributes

Deepayan Chakrabarti (University of Texas at Austin)

Learning for Counterfactual Fairness from Observational Data

Jing Ma (University of Virginia), Ruocheng Guo (Bytedance Research), Aidong Zhang (University of Virginia), Jundong Li (University of Virginia)

Online Fairness Auditing through Iterative Refinement

Pranav Maneriker (The Ohio State University), Codi Burley (The Ohio State University), Srinivasan Parthasarathy (Ohio State University)

Towards Fair Disentangled Online Learning for Changing Environments

Chen Zhao (Baylor University), Feng Mi (University of Texas at Dallas), Xintao Wu (University of Arkansas), Kai Jiang (The University of Texas at Dallas), Latifur Khan (The University of Texas at Dallas), Christan Grant (University of Florida), Feng Chen (The University of Texas at Dallas)

Wednesday, August 9, 10:00 AM-12:00 PM, Room 103C, (Recommendation with Graph). Session Chair: Jianling Wang

Meta Graph Learning for Long-Tail Recommendation

Chunyu Wei (Tsinghua University), Jian Liang (Independent Researcher), Di Liu (Alibaba Group), Zehui Dai (Alibaba Group), Mang Li (Alibaba Group), Fei Wang (Cornell University)

Graph Neural Bandits

Yunzhe Qi (University of Illinois at Urbana-Champaign), Yikun Ban (University of Illinois at Urbana-Champaign), Jingrui He (University of Illinois at Urbana-Champaign)

E-commerce Search via Content Collaborative Graph Neural Network

Guipeng Xv (School of Informatics, Xiamen University), Chen Lin (School of Informatics, Xiamen University), Wanxian Guan (Alibaba Group), Jinping Gou (Alibaba Group), Xubin Li (Alibaba Group), Hongbo Deng (Alibaba Group), Jian Xu (Alibaba Group), Bo Zheng (Alibaba Group)

Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation

Jin-Duk Park (Yonsei University), Siqing Li (The University of New South Wales), Xin Cao (The University of New South Wales), Won-Yong Shin (Yonsei University)

Knowledge Graph Self-Supervised Rationalization for Recommendation

Yuhao Yang (The University of Hong Kong), Chao Huang (The University of Hong Kong), Lianghao Xia (The University of Hong Kong), Chunzhen Huang (Tencent)

On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

Jiayan Guo (Peking University), Lun Du (Microsoft), Xu Chen (Microsoft), Xiaojun Ma (Microsoft), Qiang Fu (Microsoft), Shi Han (Microsoft), Dongmei Zhang (Microsoft), Yan Zhang (Peking University)

Wednesday, August 9, 10:00 AM-12:00 PM, Room 201A, (KDD for Security). Session Chair: Zhengzhang Chen

Towards Understanding and Enhancing Robustness of Deep Learning Models against Malicious Unlearning Attacks

Wei Qian (Iowa State University), Chenxu Zhao (Iowa State University), Wei Le (Iowa State University), Meiyi Ma (Vanderbilt University), Mengdi Huai (Iowa State University)

Incremental Causal Graph Learning for Online Root Cause Analysis

Dongjie Wang (University of Central Florida), Zhengzhang Chen (NEC Laboratories America Inc), Yanjie Fu (University of Central Florida), Yanchi Liu (NEC Laboratories America Inc), Haifeng Chen (NEC Laboratories America Inc)

Cracking White-Box DNN Watermarks via Invariant Neuron Transforms

Xudong Pan (Fudan University), Mi Zhang (Fudan University), Yifan Yan (Fudan University), Yining Wang (Fudan University), Min Yang (Fudan University)

Machine Unlearning in Gradient Boosting Decision Trees

Huawei Lin (Rochester Institute of Technology), Jun Woo Chung (Rochester Institute of Technology), Yingjie Lao (Clemson University), Weijie Zhao (Rochester Institute of Technology)

3D-IDS: Doubly Disentangled Dynamic Intrusion Detection

Chenyang Qiu (Beijing University of Posts and Telecommunications), Yingsheng Geng (Beijing University of Posts and Telecommunications), Junrui Lu (Beijing University of Posts and Telecommunications), Kaida Chen (Beijing University of Posts and Telecommunications), Shitong Zhu (Beijing University of Posts and Telecommunications), Ya Su (HUAWEI Technologies Co., Ltd.), Guoshun Nan (Beijing University of Posts and Telecommunications), Can Zhang (Beijing University of Posts and Telecommunications), Junsong Fu (Beijing University of Posts and Telecommunications), Qimei Cui (Beijing University of Posts and Telecommunications), Xiaofeng Tao (Beijing University of Posts and Telecommunications)

Wednesday, August 9, 10:00 AM-12:00 PM, Room 201B, (Time Series I). Session Chair: Shubhranshu Shekhar

Transferable Graph Structure Learning for Graph-Based Traffic Forecasting Across Cities

Yilun Jin (Hong Kong University of Science and Technology), Kai Chen (Hong Kong University of Science and Technology), Qiang Yang (Hong Kong University of Science and Technology; WeBank)

TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting

Vijay Ekambaram (IBM Research), Arindam Jati (IBM Research), Nam Nguyen (IBM Research), Phanwadee Sinthong (IBM Research), Jayant Kalagnanam (IBM Research)

Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting

Arindam Jati (IBM Research), Vijay Ekambaram (IBM Research), Shaonli Pal (Indian Institute of Technology), Brian Quanz (IBM Research), Wesley M. Gifford (IBM Research), Pavithra Harsha (IBM Research), Stuart Siegel (IBM Research), Sumanta Mukherjee (IBM Research), Chandra Narayanaswami (IBM Research)

FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework

Raneen Younis (L3S Research Center), Zahra Ahmadi (L3S Research Center), Abdul Hakmeh (University of Hildesheim), Marco Fisichella (L3S Research Center)

When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting

Harshavardhan Kamarthi (Georgia Institute of Technology), Lingkai Kong (Georgia Institute of Technology), Alexander Rodriguez (Georgia Institute of Technology), Chao Zhang (Georgia Institute of Technology), B. Aditya Prakash (Georgia Institute of Technology)

Warpformer: A Multi-Scale Modeling Approach for Irregular Clinical Time Series

Jiawen Zhang (The Hong Kong University of Science and Technology (Guangzhou)), Shun Zheng (Microsoft Research Asia), Wei Cao (Microsoft Research Asia), Jiang Bian (Microsoft Research Asia), Jia Li (The Hong Kong University of Science and Technology (Guangzhou))

SESSION 5

Wednesday, August 9, 1:30 PM-3:30 PM, Room 101B, (Knowledge and Reasoning II). Session Chair: Beiyu Lin

CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution

Yuxiang Guo (Zhejiang University), Lu Chen (Zhejiang University), Zhengjie Zhou (Zhejiang University), Baihua Zheng (Singapore Management University), Ziquan Fang (Zhejiang University), Zhikun Zhang (Stanford University), Yuren Mao (Zhejiang University), Yunjun Gao (Zhejiang University)

Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-Source Knowledge Graphs

Zequn Sun (Nanjing University), Jiacheng Huang (Nanjing University), Jinghao Lin (Alibaba Group), Xiaozhou Xu (Alibaba Group), Qijin Chen (Alibaba Group), Wei Hu (Nanjing University)

Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation

Likang Wu (University of Science and Technology of China, State Key Laboratory of Cognitive Intelligence), Zhi Li (Shenzhen International Graduate School, Tsinghua University), Hongke Zhao (Tianjin University), Zhefeng Wang (Huawei Cloud), Qi Liu (University of Science and Technology of China, State Key Laboratory of Cognitive Intelligence), Baoxing Huai (Huawei Cloud), Nicholas Jing Yuan (Huawei Cloud), Enhong Chen (University of Science and Technology of China, State Key Laboratory of Cognitive Intelligence)

Few-Shot Low-Resource Knowledge Graph Completion with Multi-view Task Representation Generation

Shichao Pei (The University of Notre Dame), Ziyi Kou (The University of Notre Dame), Qiannan Zhang (King Abdullah University of Science and Technology), Xiangliang Zhang (The University of Notre Dame)

Multi-Grained Multimodal Interaction Network for Entity Linking

Pengfei Luo (University of Science and Technology of China), Tong Xu (University of Science and Technology of China), Shiwei Wu (University of Science and Technology of China), Chen Zhu (BOSS Zhipin), Linli Xu (University of Science and Technology of China), Enhong Chen (University of Science and Technology of China)

Wednesday, August 9, 1:30 PM-3:30 PM, Room 102C, (Clustering). Session Chair: Goce Trajcevski

Prescriptive PCA: Dimensionality Reduction for Two-Stage Stochastic Optimization

Long He (George Washington University), Ho-Yin Mak (Georgetown University)

Online Level-Wise Hierarchical Clustering

Nicholas Monath (Google DeepMind), Manzil Zaheer (Google DeepMind), Andrew McCallum (Google DeepMind)

Connecting the Dots: Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering

Anna Beer (Aarhus University), Andrew Draganov (Aarhus University), Ellen Hohma (Technical University of Munich), Philipp Jahn (LMU Munich, DBS, MCML), Christian M.M. Frey (Fraunhofer IIS), Ira Assent (Aarhus University)

Spatial Clustering Regression of Count Value Data via Bayesian Mixture of Finite Mixtures

Peng Zhao (Texas AM University), Hou-Cheng Yang (Florida State University), Dipak Dey (University of Connecticut), Guanyu Hu (The University of Texas Health Science Center at Houston)

Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree

Delvin Ce Zhang (Singapore Management University), Rex Ying (Yale University), Hady W. Lauw (Singapore Management University)

Wednesday, August 9, 1:30 PM-3:30 PM, Room 103A, (Node Classification II). Session Chair: Shobeir Fakhraei

PROSE: Graph Structure Learning via Progressive Strategy

Huizhao Wang (Hikvision Research Institute), Yao Fu (Hikvision Research Institute), Tao Yu (Hikvision Research Institute), Linghui Hu (Hikvision Research Institute), Weihao Jiang (Hikvision Research Institute), Shiliang Pu (Hikvision Research Institute)

Contrastive Meta-Learning for Few-Shot Node Classification

Song Wang (University of Virginia), Zhen Tan (Arizona State University), Huan Liu (University of Virginia), Jundong Li (University of Virginia)

Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining

Jaemin Yoo (Carnegie Mellon University), Meng-Chieh Lee (Carnegie Mellon University), Shubhranshu Shekhar (Carnegie Mellon University), Christos Faloutsos (Carnegie Mellon University)

Virtual Node Tuning for Few-Shot Node Classification

Zhen Tan (Arizona State University), Ruocheng Guo (Arizona State University), Kaize Ding (Arizona State University), Huan Liu (Arizona State University)

Task-Equivariant Graph Few-Shot Learning

Sungwon Kim (KAIST), Junseok Lee (KAIST), Namkyeong Lee (KAIST), Wonjoong Kim (KAIST), Seungyoon Choi (KAIST), Chanyoung Park (KAIST)

Wednesday, August 9, 1:30 PM-3:30 PM, Room 103B, (Federated Learning & Distributed Learning I). Session Chair: Jingbo Shang

FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity

Zhen Qin (Zhejiang University), Shuiguang Deng (Zhejiang University), Mingyu Zhao (Huawei Technologies Co. Ltd.), Xueqiang Yan (Huawei Technologies Co. Ltd.)

DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization

Wenhao Zhang (Beihang University), Zimu Zhou (City University of Hong Kong), Yansheng Wang (Beihang University), Yongxin Tong (Beihang University)

FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy

Jianqing Zhang (Shanghai Jiao Tong University), Yang Hua (Queen’s University Belfast), Hao Wang (Louisiana State University), Tao Song (Shanghai Jiao Tong University), Zhengui Xue (Shanghai Jiao Tong University), Ruhui Ma (Shanghai Jiao Tong University), Haibing Guan (Shanghai Jiao Tong University)

Personalized Federated Learning with Parameter Propagation

Jun Wu (University of Illinois at Urbana-Champaign), Wenxuan Bao (University of Illinois at Urbana-Champaign), Elizabeth Ainsworth (USDA-ARS Global Change and Photosynthesis Research Unit; University of Illinois at Urbana-Champaign), Jingrui He (University of Illinois at Urbana-Champaign)

Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework

Jiayun Zhang (University of California, San Diego), Xiyuan Zhang (University of California, San Diego), Xinyang Zhang (University of Illinois at Urbana-Champaign), Dezhi Hong (Amazon), Rajesh K. Gupta (University of California, San Diego), Jingbo Shang (University of California, San Diego)

Wednesday, August 9, 1:30 PM-3:30 PM, Room 103C, (Reinforcement Learning). Session Chair: Daochen Zha

HiMacMic: Hierarchical Multi-Agent Deep Reinforcement Learning with Dynamic Asynchronous Macro Strategy

Hancheng Zhang (Beijing Inst. of Tech.), Guozheng Li (Beijing Inst. of Tech.), Chi Harold Liu (Beijing Inst. of Tech.), Guoren Wang (Beijing Inst. of Tech.), Jian Tang (Midea Group)

GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning

Qianyue Hao (Tsinghua University), Wenzhen Huang (Tsinghua University), Tao Feng (Tsinghua University), Jian Yuan (Tsinghua University, Tsinghua University), Yong Li (Tsinghua University)

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations

Tianxiang Zhao (the Pennsylvania State University), Wenchao Yu (NEC-Labs America), Suhang Wang (the Pennsylvania State University), Lu Wang (East China Normal University), Xiang Zhang (the Pennsylvania State University), Yuncong Chen (NEC-Labs America), Yanchi Liu (NEC-Labs America), Wei Cheng (NEC-Labs America), Haifeng Chen (NEC-Labs America)

Internal Logical Induction for Pixel-Symbolic Reinforcement Learning

Jiacheng Xu (Nanjing University), Chao Chen (Nanjing University), Fuxiang Zhang (Nanjing University), Lei Yuan (Nanjing University; Polixir Technologies), Zongzhang Zhang (Nanjing University), Yang Yu (Nanjing University; Polixir Technologies)

Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay

Thomas M. McDonald (University of Manchester), Lucas Maystre (Spotify), Mounia Lalmas (Spotify), Daniel Russo (University of Columbia; Spotify), Kamil Ciosek (Spotify)

Towards Variance Reduction for Reinforcement Learning of Industrial Decision-Making Tasks: A Bi-Critic based Demand-Constraint Decoupling Approach

Jianyong Yuan (Shanghai Jiao Tong University), Jiayi Zhang (Shanghai Jiao Tong University), Zinuo Cai (Shanghai Jiao Tong University), Junchi Yan (Shanghai Jiao Tong University)

Wednesday, August 9, 1:30 PM-3:30 PM, Room 201A, (KDD for Drug Discovery and Development). Session Chair: Lifang He

Dual-view Molecular Pre-training

Jinhua Zhu (University of Science and Technology of China), Yingce Xia (Microsoft Research AI4Science), Lijun Wu (Microsoft Research AI4Science), Shufang Xie (Renmin University of China), Wengang Zhou (University of Science and Technology of China), Tao Qin (Microsoft Research AI4Science), Houqiang Li (University of Science and Technology of China), Tie-Yan Liu (Microsoft Research AI4Science)

Shift-Robust Molecular Relational Learning with Causal Substructure

Namkyeong Lee (KAIST), Kanghoon Yoon (KAIST), Gyoung S. Na (KRICT), Sein Kim (KAIST), Chanyoung Park (KAIST)

Accelerating Antimicrobial Peptide Discovery with Latent Structure

Danqing Wang (University of California, Santa Barbara), Zeyu Wen (Huazhong University of Science and Technology), Fei Ye (ByteDance Research), Lei Li (University of California, Santa Barbara), Hao Zhou (Institute for AI Industry Research, Tsinghua University)

ExplainableFold: Understanding AlphaFold Prediction with Explainable AI

Juntao Tan (Rutgers University), Yongfeng Zhang (Rutgers University)

Automated 3D Pre-Training for Molecular Property Prediction

Xu Wang (4Paradigm Inc.), Huan Zhao (4Paradigm Inc.), Wei-Wei Tu (4Paradigm Inc.), Quanming Yao (Tsinghua University)

Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design

Kaiyuan Gao (School of Computer Science and Technology, Huazhong University of Science and Technology), Lijun Wu (Microsoft Research AI4Science), Jinhua Zhu (CAS Key Laboratory of GIPAS, University of Science and Technology of China), Tianbo Peng (School of Life Sciences and Biomedical Pioneering Innovation Center, Peking University), Yingce Xia (Microsoft Research AI4Science), Liang He (Microsoft Research AI4Science), Shufang Xie (Microsoft Research AI4Science), Tao Qin (Microsoft Research AI4Science), Haiguang Liu (Microsoft Research AI4Science), Kun He (School of Computer Science and Technology, Huazhong University of Science and Technology), Tie-Yan Liu (Microsoft Research AI4Science)

Wednesday, August 9, 1:30 PM-3:30 PM, Room 201B, (Time Series II). Session Chair: Qingsong Wen

WHEN: A Wavelet-DTW Hybrid Attention Network for Heterogeneous Time Series Analysis

Jingyuan Wang (Beihang University; Ministry of Industry and Information Technology), Chen Yang (Beihang University), Xiaohan Jiang (Beihang University), Junjie Wu (Beihang University; Ministry of Industry and Information Technology)

Source-Free Domain Adaptation with Temporal Imputation for Time Series Data

Mohamed Ragab (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR)), Emadeldeen Eldele (Center for Frontier AI Research, Agency for Science and Technology and Research (A*STAR)), Min Wu (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR)), Chuan-Sheng Foo (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR)), Xiaoli Li (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR)), Zhenghua Chen (Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR))

Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders

Dingsu Wang (University of Illinois at Urbana-Champaign), Yuchen Yan (University of Illinois at Urbana-Champaign), Ruizhong Qiu (University of Illinois at Urbana-Champaign), Yada Zhu (IBM Research), Kaiyu Guan (University of Illinois at Urbana-Champaign), Andrew Margenot (University of Illinois at Urbana-Champaign), Hanghang Tong (University of Illinois at Urbana-Champaign)

Sparse Binary Transformers for Multivariate Time Series Modeling

Matt Gorbett (Colorado State University), Hossein Shirazi (Colorado State University), Indrakshi Ray (Colorado State University)

Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models

Chunjing Xiao (Henan University), Zehua Gou (Henan University), Wenxin Tai (University of Electronic Science and Technology of China), Kunpeng Zhang (University of Maryland, College Park), Fan Zhou (University of Electronic Science and Technology of China)

An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series

Xu Wang (University of Science and Technology of China), Hongbo Zhang (University of Science and Technology of China), Pengkun Wang (University of Science and Technology of China; Suzhou Institute for Advanced Research, USTC), Yudong Zhang (University of Science and Technology of China), Binwu Wang (University of Science and Technology of China), Zhengyang Zhou (University of Science and Technology of China; Suzhou Institute for Advanced Research, USTC), Yang Wang (University of Science and Technology of China; Suzhou Institute for Advanced Research, USTC)

SESSION 6

Wednesday, August 9, 4:00 PM-6:00 PM, Room 101B, (Misinformation and Disinformation). Session Chair: Tsuyoshi Ide

Preemptive Detection of Fake Accounts on Social Networks via Multi-Class Preferential Attachment Classifiers

Adam Breuer (Dartmouth), Nazanin Khosravani (Meta), Michael Tingley (Meta), Bradford Cottel (Meta)

Rumor Detection with Diverse Counterfactual Evidence

Kaiwei Zhang (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences), Junchi Yu (MAISCRIPAC, Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences), Haichao Shi (Institute of Information Engineering, Chinese Academy of Sciences), Jian Liang (MAISCRIPAC, Institute of Automation, Chinese Academy of Sciences), Xiao-Yu Zhang (Institute of Information Engineering, Chinese Academy of Sciences)

Adversaries with Limited Information in the Friedkin-Johnsen Model

Sijing Tu (KTH Royal Institute of Technology), Stefan Neumann (KTH Royal Institute of Technology), Aristides Gionis (KTH Royal Institute of Technology)

Shilling Black-Box Review-Based Recommender Systems through Fake Review Generation

Hung-Yun Chiang (National Tsing Hua University), Yi-Syuan Chen (National Yang Ming Chiao Tung University), Yun-Zhu Song (National Yang Ming Chiao Tung University), Hong-Han Shuai (National Yang Ming Chiao Tung University), Jason S. Chang (National Tsing Hua University)

Maximizing Neutrality in News Ordering

Rishi Advani (University of Illinois Chicago), Paolo Papotti (EURECOM), Abolfazl Asudeh (University of Illinois Chicago)

DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection

Jiaying Wu (National University of Singapore), Bryan Hooi (National University of Singapore)

Wednesday, August 9, 4:00 PM-6:00 PM, Room 102C, (Conversational AI). Session Chair: Qiaoyu Tan

Improving Conversational Recommendation Systems via Counterfactual Data Simulation

Xiaolei Wang (Renmin University of China), Kun Zhou (Renmin University of China), Xinyu Tang (Renmin University of China), Wayne Xin Zhao (Renmin University of China), Fan Pan (Huawei Poisson Lab), Zhao Cao (Huawei Poisson Lab), Ji-Rong Wen (Renmin University of China)

Improving Search Clarification with Structured Information Extracted from Search Results

Ziliang Zhao (Renmin University of China), Zhicheng Dou (Renmin University of China), Yu Guo (Renmin University of China), Zhao Cao (Huawei Poisson Lab), Xiaohua Cheng (Huawei Poisson Lab)

LATTE: A Framework for Learning Item-Features to Make a Domain-Expert for Effective Conversational Recommendation

Taeho Kim (Hanyang University), Juwon Yu (Hanyang University), Won-Yong Shin (Yonsei University), Hyunyoung Lee (KT Corporation), Ji-hui Im (KT Corporation), Sang-Wook Kim (Hanyang University)

Delving into Global Dialogue Structures: Structure Planning Augmented Response Selection for Multi-Turn Conversations

Tingchen Fu (Gaoling School of AI (GSAI), Renmin University of China), Xueliang Zhao (Peking University), Rui Yan (Gaoling School of AI (GSAI), Renmin University of China; Engineering Research Center of Next-Generation Intelligent Search and Recommendation, Ministry of Education)

Learning to Relate to Previous Turns in Conversational Search

Fengran Mo (University of Montreal), Jian-Yun Nie (University of Montreal), Kaiyu Huang (Tsinghua University), Kelong Mao (Renmin University of China), Yutao Zhu (University of Montreal), Peng Li (Tsinghua University), Yang Liu (Tsinghua University)

User-Regulation Deconfounded Conversational Recommender System with Bandit Feedback

Yu Xia (Shanghai Jiao Tong University), Junda Wu (New York University), Tong Yu (Adobe Research), Sungchul Kim (Adobe Research), Ryan A. Rossi (Adobe Research), Shuai Li (Shanghai Jiao Tong University)

Wednesday, August 9, 4:00 PM-6:00 PM, Room 103A, (Out-of-Distribution). Session Chair: Feng Chen

Domain-Specific Risk Minimization for Domain Generalization

Yi-Fan Zhang (Institute of Automation), Jindong Wang (Microsoft Research Asia; University of Chinese Academy of Sciences), Jian Liang (Institute of Automation), Zhang Zhang (Institute of Automation), Baosheng Yu (The University of Sydney), Liang Wang (Institute of Automation), Dacheng Tao (The University of Sydney), Xing Xie (Microsoft Research Asia)

Causal Inference via Style Transfer for Out-of-Distribution Generalisation

Toan Nguyen (Applied Artificial Intelligence Institute, Deakin University), Kien Do (Applied Artificial Intelligence Institute, Deakin University), Duc Thanh Nguyen (School of Information Technology, Deakin University), Bao Duong (Applied Artificial Intelligence Institute, Deakin University), Thin Nguyen (Applied Artificial Intelligence Institute, Deakin University)

FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs

Yang Liu (Institute of Computing Technology, CAS), Xiang Ao (Institute of Computing Technology, CAS), Fuli Feng (Institute of Computing Technology, CAS), Yunshan Ma (Institute of Computing Technology, CAS), Kuan Li (Institute of Computing Technology, CAS), Tat-seng Chua (Institute of Computing Technology, CAS), Qing He (Institute of Computing Technology, CAS)

Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization

Yunze Tong (Zhejiang University), Junkun Yuan (Zhejiang University), Min Zhang (Zhejiang University), Didi Zhu (Zhejiang University), Keli Zhang (Noah’s Ark Lab, Huawei Technologies), Fei Wu (Zhejiang University), Kun Kuang (Zhejiang University)

A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability

Yuxin Guo (Beijing University of Posts and Telecommunications), Cheng Yang (Beijing University of Posts and Telecommunications), Yuluo Chen (Beijing University of Posts and Telecommunications), Jixi Liu (Beijing University of Posts and Telecommunications), Chuan Shi (Beijing University of Posts and Telecommunications), Junping Du (Beijing University of Posts and Telecommunications)

Wednesday, August 9, 4:00 PM-6:00 PM, Room 103B, (Federated Learning & Distributed Learning II). Session Chair: Wei Cheng

CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning

Gang Yan (State University of New York, Binghamton), Hao Wang (Louisiana State University), Xu Yuan (University of Louisiana at Lafayette), Jian Li (State University of New York, Binghamton)

Federated Few-Shot Learning

Song Wang (University of Virginia), Xingbo Fu (University of Virginia), Kaize Ding (Arizona State University), Chen Chen (University of Virginia), Huiyuan Chen (Case Western Reserve University), Jundong Li (University of Virginia)

FedDefender: Client-Side Attack-Tolerant Federated Learning

Sungwon Park (KAIST), Sungwon Han (KAIST), Fangzhao Wu (Microsoft Research Asia), Sundong Kim (GIST), Bin Zhu (Microsoft Research Asia), Xing Xie (Microsoft Research Asia), Meeyoung Cha (IBS; KAIST)

Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining

Xidong Wu (University of Pittsburgh), Zhengmian Hu (University of Pittsburgh), Jian Pei (Duke University), Heng Huang (University of Maryland, College Park)

Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity

Yangyang Wang (Shandong University), Xiao Zhang (Shandong University), Mingyi Li (Shandong University), Tian Lan (George Washington University), Huashan Chen (Chinese Academy of Sciences), Hui Xiong (Hong Kong University of Science and Technology), Xiuzhen Cheng (Shandong University), Dongxiao Yu (Shandong University)

ShapleyFL: Robust Federated Learning Based on Shapley Value

Qiheng Sun (Zhejiang University), Xiang Li (Zhejiang University), Jiayao Zhang (Zhejiang University), Li Xiong (Emory University), Weiran Liu (Alibaba Group), Jinfei Liu (Zhejiang University; ZJU-Hangzhou Global Scientific and Technological Innovation Center), Zhan Qin (Zhejiang University), Kui Ren (Zhejiang University)

Wednesday, August 9, 4:00 PM-6:00 PM, Room 103C, (Responsible Recommendation). Session Chair: Ruirui Li

Hierarchical Invariant Learning for Domain Generalization Recommendation

Zeyu Zhang (Renmin University of China), Heyang Gao (Beijing University of Posts and Telecommunications), Hao Yang (Renmin University of China), Xu Chen (Renmin University of China)

UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation

Jiacheng Li (University of California, San Diego), Zhankui He (University of California, San Diego), Jingbo Shang (University of California, San Diego), Julian McAuley (University of California, San Diego)

Debiasing Recommendation by Learning Identifiable Latent Confounders

Qing Zhang (Hong Kong University of Science and Technology), Xiaoying Zhang (ByteDance Research), Yang Liu (ByteDance Research), Hongning Wang (University of Virginia), Min Gao (Chongqing University), Jiheng Zhang (Hong Kong University of Science and Technology), Ruocheng Guo (ByteDance Research)

Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective

Teng Xiao (The Pennsylvania State University), Zhengyu Chen (Zhejiang University), Suhang Wang (The Pennsylvania State University)

Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation

Haoxuan Li (Peking University), Chunyuan Zheng (University of California, San Diego), Peng Wu (Beijing Technology and Business University), Kun Kuang (Zhejiang University), Yue Liu (Renmin University of China), Peng Cui (Tsinghua University)

Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction

Yifan Wang (Tsinghua University), Peijie Sun (Tsinghua University), Min Zhang (Tsinghua University), Qinglin Jia (Noah’s Ark Lab, Huawei), Jingjie Li (Noah’s Ark Lab, Huawei), Shaoping Ma (Tsinghua University)

Wednesday, August 9, 4:00 PM-6:00 PM, Room 201A, (KDD for Finance). Session Chair: Guansong Pang

Mastering Stock Markets with Efficient Mixture of Diversified Trading Experts

Shuo Sun (Nanyang Technological University), Xinrun Wang (Nanyang Technological University), Wanqi Xue (Nanyang Technological University), Xiaoxuan Lou (Nanyang Technological University), Bo An (Nanyang Technological University)

Financial Default Prediction via Motif-Preserving Graph Neural Network with Curriculum Learning

Daixin Wang (Ant Group), Zhiqiang Zhang (Ant Group), Yeyu Zhao (Ant Group), Kai Huang (Ant Group), Yulin Kang (Ant Group), Jun Zhou (Ant Group)

DoubleAdapt: A Meta-Learning Approach to Incremental Learning for Stock Trend Forecasting

Lifan Zhao (Shanghai Jiao Tong University), Shuming Kong (Shanghai Jiao Tong University), Yanyan Shen (Shanghai Jiao Tong University)

Towards Reliable Rare Category Analysis on Graphs via Individual Calibration

Longfeng Wu (Virginia Tech), Bowen Lei (Texas AM University), Dongkuan Xu (North Carolina State University), Dawei Zhou (Virginia Tech)

QTIAH-GNN: Quantity and Topology Imbalance-Aware Heterogeneous Graph Neural Network for Bankruptcy Prediction

Yucheng Liu (University of Science and Technology of China), Zipeng Gao (University of Science and Technology of China), Xiangyang Liu (University of Science and Technology of China), Pengfei Luo (University of Science and Technology of China ), Yang Yang (Nanjing University of Science and Technology; The Hong Kong Polytechnic University), Hui Xiong (The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology)

Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning

Haozhe Wang (Alibaba Group), Chao Du (Alibaba Group), Panyan Fang (Alibaba Group), LI He (Alibaba Group), Liang Wang (Alibaba Group), Bo Zheng (Alibaba Group)

Wednesday, August 9, 4:00 PM-6:00 PM, Room 201B, (User Modeling, Web and E-commerce). Session Chair: Jaemin Yoo

Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling

Chaofan Fu (Ocean University of China), Guanjie Zheng (Shanghai Jiao Tong University), Chao Huang (The University of Hong Kong), Yanwei Yu (Ocean University of China), Junyu Dong (Ocean University of China)

End-to-End Inventory Prediction and Contract Allocation for Guaranteed Delivery Advertising

Wuyang Mao (Alibaba Group), Chuanren Liu (The University of Tennessee), Yundu Huang (Alibaba Group), Zhonglin Zu (Alibaba Group), M Harshvardhan (The University of Tennessee), Liang Wang (Alibaba Group), Bo Zheng (Alibaba Group)

Contrastive Learning for User Sequence Representation in Personalized Product Search

Shitong Dai (Renmin University of China), Jiongnan Liu (Renmin University of China), Zhicheng Dou (Renmin University of China), Haonan Wang (JD.com, Inc.), Lin Liu (JD.com, Inc.), Bo Long (JD.com, Inc.), Ji-Rong Wen (Engineering Research Center of Next-Generation Intelligent Search and Recommendation, Ministry of Education)

Empowering General-purpose User Representation with Full-life Cycle Behavior Modeling

Bei Yang (Alibaba Group), Jie Gu (Alibaba Group), Ke Liu (Zhejiang University), Xiaoxiao Xu (Alibaba Group), Renjun Xu (Zhejiang University), Qinghui Sun (Alibaba Group), Hong Liu (Alibaba Group)

Task Relation-aware Continual User Representation Learning

Sein Kim (KAIST), Namkyeong Lee (KAIST), Donghyun Kim (NAVER Corporation), Min-Chul Yang (NAVER Corporation), Chanyoung Park (KAIST)

Learning-Based Ad Auction Design with Externalities: The Framework and a Matching-Based Approach

Ningyuan Li (Peking University), Yunxuan Ma (Peking University), Yang Zhao (Alibaba Group), Zhijian Duan (Peking University), Yurong Chen (Peking University), Zhilin Zhang (Alibaba Group), Jian Xu (Alibaba Group), Bo Zheng (Alibaba Group), Xiaotie Deng (Peking University)

SESSION 7

Thursday, August 10, 10:00 AM-12:00 PM, Room 101B, (Large Scale Data). Session Chair: David C. Anastasiu

Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems

Peng Peng (Hunan University), Shengyi Ji (Hunan University), Zhen Tian (Hunan University), Hongbo Jiang (Hunan University), Weiguo Zheng (Fudan University), Xuecang Zhang (Huawei Technologies)

Efficient Single-Source SimRank Query by Path Aggregation

Mingxi Zhang (University of Shanghai for Science and Technology), Yanghua Xiao (Fudan University), Wei Wang (Fudan University)

DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication

Igor Nunes (University of California, Irvine), Mike Heddes (University of California, Irvine), Pere Vergés (University of California, Irvine), Danny Abraham (University of California, Irvine), Alex Veidenbaum (University of California, Irvine), Alex Nicolau (University of California, Irvine), Tony Givargis (University of California, Irvine)

OPORP: One Permutation + One Random Projection

Ping Li (LinkedIn Ads), Xiaoyun Li (LinkedIn Ads)

Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest

Sang-Hong Kim (Kookmin University), Ha-Myung Park (Kookmin University)

Learning Balanced Tree Indexes for Large-Scale Vector Retrieval

Wuchao Li (University of Science and Technology of China), Chao Feng (University of Science and Technology of China), Defu Lian (University of Science and Technology of China), Yuxin Xie (Guangdong OPPO Mobile Telecommunications Corp., Ltd), Haifeng Liu (Guangdong OPPO Mobile Telecommunications Corp., Ltd), Yong Ge (University of Arizona), Enhong Chen (University of Science and Technology of China)

Thursday, August 10, 10:00 AM-12:00 PM, Room 102C, (Dynamic and Heterogenous Network). Session Chair: Kijung Shin

Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds

Haoran Deng (Zhejiang University), Yang Yang (Zhejiang University), Jiahe Li (Zhejiang University), Haoyang Cai (Carnegie Mellon University), Shiliang Pu (Hikvision Research Institute), Weihao Jiang (Hikvision Research Institute)

Fairness-Aware Continuous Predictions of Multiple Analytics Targets in Dynamic Networks

Ruifeng Liu (University of Massachusetts at Lowell), Qu Liu (University of Massachusetts at Lowell), Tingjian Ge (University of Massachusetts at Lowell)

DyTed: Disentangled Representation Learning for Discrete-Time Dynamic Graph

Kaike Zhang (Institute of Computing Technology, Chinese Academy of Sciences; The University of Chinese Academy of Sciences), Qi Cao (Institute of Computing Technology, Chinese Academy of Sciences), Gaolin Fang (Tencent Inc.), Xu Bingbing (Institute of Computing Technology, Chinese Academy of Sciences), Hongjian Zou (Tencent Inc.), Huawei Shen (Institute of Computing Technology, Chinese Academy of Sciences), Xueqi Cheng (Institute of Computing Technology, Chinese Academy of Sciences)

Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks

Bowen Jin (University of Illinois at Urbana-Champaign), Yu Zhang (University of Illinois at Urbana-Champaign), Qi Zhu (University of Illinois at Urbana-Champaign), Jiawei Han (University of Illinois at Urbana-Champaign)

Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation

Qiang Yang (King Abdullah University of Science and Technology), Changsheng Ma (King Abdullah University of Science and Technology), Qiannan Zhang (King Abdullah University of Science and Technology), Xin Gao (King Abdullah University of Science and Technology), Chuxu Zhang (Brandeis University), Xiangliang Zhang (University of Notre Dame; King Abdullah University of Science and Technology)

WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window

Yifan Zhu (Tsinghua University), Fangpeng Cong (Yanshan University), Dan Zhang (Tsinghua University), Wenwen Gong (Tsinghua University), Qika Lin (Xi’an Jiaotong University), Wenzheng Feng (Tsinghua University), Yuxiao Dong (Tsinghua University), Jie Tang (Tsinghua University)

Thursday, August 10, 10:00 AM-12:00 PM, Room 103A, (Patterns and Motifs). Session Chair: Jian Kang

EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation

Kuo Yang (University of Science and Technology of China), Zhengyang Zhou (Suzhou Institute for Advanced Research, University of Science and Technology of China), Wei Sun (University of Science and Technology of China), Pengkun Wang (Suzhou Institute for Advanced Research, University of Science and Technology of China), Xu Wang (University of Science and Technology of China), Yang Wang (University of Science and Technology of China)

Parameter-free Spikelet: Discovering Different Length and Warped Time Series Motifs using an Adaptive Time Series Representation

Makoto Imamura (Tokai University Educational System), Takaaki Nakamura (Mitsubishi Electric Corporation )

Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns

Joscha Cüppers (CISPA Helmholtz Center for Information Security), Jilles Vreeken (CISPA Helmholtz Center for Information Security)

Using Motif Transitions for Temporal Graph Generation

Penghang Liu (University at Buffalo), Ahmet Erdem Sariyuce (University at Buffalo)

MimoSketch: A Framework to Mine Item Frequency on Multiple Nodes with Sketches

Yuchen Xu (Peking University), Wenfei Wu (Peking University), Bohan Zhao (Tsinghua University), Tong Yang (Peking University), Yikai Zhao (Peking University)

Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation

Pengtao Dang (Purdue University), Haiqi Zhu (Indiana University), Tingbo Guo (Indiana University), Changlin Wan (Purdue University), Tong Zhao (Uber Inc.), Paul Salama (Purdue University), Yijie Wang (Indiana University), Sha Cao (Indiana University), Chi Zhang (Indiana University)

Thursday, August 10, 10:00 AM-12:00 PM, Room 103B, (Geometric and Brain Data). Session Chair: Dawei Zhou

3D-Polishing for Triangular Mesh Compression of Point Cloud Data

Jiaqi Gu (Stanford University), Guosheng Yin (Imperial College London)

Domain-Guided Spatio-Temporal Self-Attention for Egocentric 3D Pose Estimation

Jinman Park (University of Waterloo), Kimathi Kaai (University of Waterloo), Saad Hossain (University of Waterloo), Norikatsu Sumi (Nissan Motor Corporation), Sirisha Rambhatla (University of Waterloo), Paul Fieguth (University of Waterloo)

Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks

Gaotang Li (University of Michigan, Ann Arbor), Marlena Duda (Georgia State University), Xiang Zhang (University of North Carolina, Charlotte), Danai Koutra (University of Michigan, Ann Arbor), Yujun Yan (Dartmouth College)

One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data

Yao Su (Worcester Polytechnic Institute), Zhentian Qian (Worcester Polytechnic Institute), Lei Ma (Worcester Polytechnic Institute), Lifang He (Lehigh University), Xiangnan Kong (Worcester Polytechnic Institute)

MBrain: A Multi-Channel Self-Supervised Learning Framework for Brain Signals

Donghong Cai (Zhejiang University), Junru Chen (Zhejiang University), Yang Yang (Zhejiang University), Teng Liu (Zhejiang University), Yafeng Li (Nuozhu Technology Co., Ltd.)

Thursday, August 10, 10:00 AM-12:00 PM, Room 103C, (Robust ML I). Session Chair: Kai Shu

PAT: Geometry-Aware Hard-Label Black-Box Adversarial Attacks on Text

Muchao Ye (The Pennsylvania State University), Jinghui Chen (The Pennsylvania State University), Chenglin Miao (Iowa State University), Han Liu (Dalian University of Technology), Ting Wang (The Pennsylvania State University), Fenglong Ma (The Pennsylvania State University)

Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks

Yaning Jia (Huazhong University of Science and Technology), Dongmian Zou (Duke Kunshan University), Hongfei Wang (Huazhong University of Science and Technology), Hai Jin (Huazhong University of Science and Technology)

Robustness Certification for Structured Prediction with General Inputs via Safe Region Modeling in the Semimetric Output Space

HUAQING SHAO (Shanghai Jiao Tong University), Lanjun Wang (Tianjin University), Junchi Yan (Shanghai Jiao Tong University)

Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models

Kartik Sharma (Georgia Institute of Technology), Rakshit Trivedi (Massachusetts Institute of Technology), Rohit Sridhar (Georgia Institute of Technology), Srijan Kumar (Georgia Institute of Technology)

Investigating Trojan Attacks on Pre-trained Language Model-powered Database Middleware

Peiran Dong (Hong Kong Polytechnic University), Song Guo (Hong Kong Polytechnic University), Junxiao Wang (King Abdullah University of Science and Technology)

A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy

Enyan Dai (Pennsylvania State University), Limeng Cui (Amazon), Zhengyang Wang (Amazon), Xianfeng Tang (Amazon), Yinghan Wang (Amazon), Monica Cheng (Amazon), Bing Yin (Amazon), Suhang Wang (Pennsylvania State University)

Thursday, August 10, 10:00 AM-12:00 PM, Room 201A, (KDD for Healthcare). Session Chair: Lichao Sun

Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes

Song Wei (Georgia Institute of Technology), Yao Xie (Georgia Institute of Technology), Christopher S Josef (Emory University), Rishikesan Kamaleswaran (Emory University)

TWIN: Personalized Clinical Trial Digital Twin Generation

Trisha Das (University of Illinois Urbana-Champaign), Zifeng Wang (University of Illinois Urbana-Champaign), Jimeng Sun (University of Illinois Urbana-Champaign)

R-Mixup: Riemannian Mixup for Biological Networks

Xuan Kan (Emory University), Zimu Li (University of Chicago), Hejie Cui (Emory University), Yue Yu (Georgia Institute of Technology), Ran Xu (Emory University), Shaojun Yu (Emory University), Zilong Zhang (University of International Business and Economics), Ying Guo (Emory University), Carl Yang (Emory University)

Web-Based Long-Term Spine Treatment Outcome Forecasting

Hangting Ye (Jilin University), Zhining Liu (University of Illinois Urbana-Champaign), Wei Cao (Microsoft Research), Amir M. Amiri (Microsoft Research), Jiang Bian (Microsoft Research), Yi Chang (Jilin University), Jon D. Lurie (The Dartmouth Institute), Jim Weinstein (Microsoft Research), Tie-Yan Liu (Microsoft Research)

MedLink: De-Identified Patient Health Record Linkage

Zhenbang Wu (University of Illinois Urbana-Champaign), Cao Xiao (Relativity), Jimeng Sun (University of Illinois Urbana-Champaign)

FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis

Md Mahmudur Rahman (University of Maryland, Baltimore County), Sanjay Purushotham (University of Maryland, Baltimore County)

Thursday, August 10, 10:00 AM-12:00 PM, Room 201B, (Urban Data I). Session Chair: Yuxuan Liang

Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training

Fan Liu (The Hong Kong University of Science and Technology (Guangzhou)), Weijia Zhang (The Hong Kong University of Science and Technology (Guangzhou)), Hao Liu (The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology)

Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction

Binwu Wang (University of Science and Technology of China), Yudong Zhang (University of Science and Technology of China), Xu Wang (University of Science and Technology of China), Pengkun Wang (Suzhou Institute for Advanced Research, University of Science and Technology of China), Zhengyang Zhou (Suzhou Institute for Advanced Research, University of Science and Technology of China), LEI BAI (Shanghai AI Laboratory), Yang Wang (University of Science and Technology of China)

TransformerLight: A Novel Sequence Modeling Based Traffic Signaling Mechanism via Gated Transformer

Qiang Wu (University of Electronic Science and Technology of China), Mingyuan Li (Beijing University of Posts and Telecommunications), Jun Shen (University of Wollongong), Linyuan L (University of Science and Technology of China), Bo Du (University of Wollongong), Ke Zhang (Beijing University of Posts and Telecommunications)

Optimizing Traffic Control with Model-Based Learning: A Pessimistic Approach to Data-Efficient Policy Inference

Mayuresh Kunjir (Amazon Web Services), Sanjay Chawla (Qatar Computing Research Institute, Hamad Bin Khalifa University), Siddarth Chandrasekar (Indian Institute of Technology Madras), Devika Jay (Indian Institute of Technology Madras), Balaraman Ravindran (Indian Institute of Technology Madras)

Mitigating Action Hysteresis in Traffic Signal Control with Traffic Predictive Reinforcement Learning

Xiao Han (City University of Hong Kong), Xiangyu Zhao (City University of Hong Kong), Liang Zhang (Shenzhen Research Institute of Big Data), Wanyu Wang (City University of Hong Kong)

Spatial Heterophily Aware Graph Neural Networks

Congxi Xiao (University of Science and Technology of China; Baidu Research), Jingbo Zhou (Baidu Research), Jizhou Huang (Baidu Inc.), Tong Xu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Hui Xiong (The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology)

SESSION 8

Thursday, August 10, 1:30 PM-3:30 PM, Room 101B, (Multi-Task and Transfer Learning). Session Chair: Jeremy Lee

MAPLE: Semi-Supervised Learning with Multi-Alignment and Pseudo-Learning

Juncheng Yang (School of Computer Science, Wuhan University), Chao Li (JD Health International Inc.), Zuchao Li (National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University), Wei Yu (School of Computer Science, Wuhan University), Bo Du (National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University), Shijun Li (School of Computer Science, Wuhan University)

Leveraging Relational Graph Neural Network for Transductive Model Ensemble

Zhengyu Hu (Mohamed bin Zayed University of Artificial Intelligence), Jieyu Zhang (University of Washington), Haonan Wang (National University of Singapore), Siwei Liu (Mohamed bin Zayed University of Artificial Intelligence), Shangsong Liang (Mohamed bin Zayed University of Artificial Intelligence; Sun Yat-sen University)

Automatic Temporal Relation in Multi-Task Learning

Menghui Zhou (The University of Sheffield), Po Yang (The University of Sheffield)

When to Pre-Train Graph Neural Networks? From Data Generation Perspective!

Yuxuan Cao (Zhejiang University; Fudan University), Jiarong Xu (Fudan University), Carl Yang (Emory University), Jiaan Wang (Soochow University), Yunchao Zhang (Zhejiang University), Chunping Wang (Finvolution Group), Lei CHEN (Finvolution Group), Yang Yang (Zhejiang University)

Boosting Multitask Learning on Graphs through Higher-Order Task Affinities

Dongyue Li (Northeastern University), Haotian Ju (Northeastern University), Aneesh Sharma (Google), Hongyang R. Zhang (Northeastern University)

Thursday, August 10, 1:30 PM-3:30 PM, Room 102C, (Dynamic Process). Session Chair: Yushun Dong

Graph Neural Processes for Spatio-Temporal Extrapolation

Junfeng Hu (National University of Singapore), Yuxuan Liang (Hong Kong University of Science and Technology (Guangzhou)), Zhencheng Fan (University of Technology Sydney), Hongyang Chen (Zhejiang Lab), Yu Zheng (JD Intelligent Cities Research; JD iCity, JD Technology), Roger Zimmermann (National University of Singapore)

Reconstructing Graph Diffusion History from a Single Snapshot

Ruizhong Qiu (University of Illinois Urbana-Champaign), Dingsu Wang (University of Illinois Urbana-Champaign), Lei Ying (University of Michigan), H. Vincent Poor (Princeton University), Yifang Zhang (C3.ai Digital Transformation Institute), Hanghang Tong (University of Illinois Urbana-Champaign)

Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations

Yingtao Luo (Carnegie Mellon University), Qiang Liu (CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences), Yuntian Chen (Ningbo Institute of Digital Twin, Eastern Institute of Technology), Wenbo Hu (Hefei University of Technology), Tian Tian (RealAI), Jun Zhu (Tsinghua University)

Learning to Schedule in Diffusion Probabilistic Models

Yunke Wang (Wuhan University), Xiyu Wang (The University of Sydney), Anh-Dung Dinh (The University of Sydney), Bo Du (Wuhan University), Charles Xu (The University of Sydney)

Generalizing Graph ODE for Learning Complex System Dynamics across Environments

Zijie Huang (University of California, Los Angeles), Yizhou Sun (University of California, Los Angeles), Wei Wang (University of California, Los Angeles)

Deep Bayesian Active Learning for Accelerating Stochastic Simulation

Dongxia Wu (University of California, San Diego), Ruijia Niu (University of California, San Diego), Matteo Chinazzi (Northeastern University), Alessandro Vespignani (Northeastern University), Yi-An Ma (University of California, San Diego), Rose Yu (University of California, San Diego)

Thursday, August 10, 1:30 PM-3:30 PM, Room 103A, (Privacy). Session Chair: Haohan Wang

Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations

Vy Vo (Monash University), Trung Le (Monash University), Van Nguyen (Monash University), He Zhao (CSIROÊäØ Data61), Edwin V. Bonilla (CSIROÊäØ Data61), Gholamreza Haffari (Monash University), Dinh Phung (Monash University)

Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting

Ergute Bao (National University of Singapore), Dawei Gao (Alibaba Group), Xiaokui Xiao (National University of Singapore), Yaliang Li (Alibaba Group)

Unbiased Locally Private Estimator for Polynomials of Laplacian Variables

Quentin Hillebrand (The University of Tokyo), Vorapong Suppakitpaisarn (The University of Tokyo), Tetsuo Shibuya (The University of Tokyo)

Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation

Zeyu Cao (University of Cambridge), Zhipeng Liang (Hong Kong University of Science and Technology), Bingzhe Wu (Tencent AI Lab), Shu Zhang (Tencent AI Lab), Hangyu Li (Tencent AI Lab), Ouyang Wen (Tencent AI Lab), Yu Rong (Tencent AI Lab), Peilin Zhao (Tencent AI Lab)

FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation

Yushan Jiang (University of Connecticut), Wenchao Yu (NEC Labs America), Dongjin Song (University of Connecticut), Lu Wang (East China Normal University), Wei Cheng (NEC Labs America), Haifeng Chen (NEC Labs America)

Thursday, August 10, 1:30 PM-3:30 PM, Room 103B, (Graph Contrastive Learning). Session Chair: Wei Jin

B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning

Mengyue Liu (Xi’an Jiaotong University), Yun Lin (Shanghai Jiao Tong University), Jun Liu (Xi’an Jiaotong University), Bohao Liu (Xi’an Jiaotong University), Qinghua Zheng (Xi’an Jiaotong University), Jin Song Dong (National University of Singapore)

Similarity Preserving Adversarial Graph Contrastive Learning

Yeonjun In (KAIST), Kanghoon Yoon (KAIST), Chanyoung Park (KAIST)

HomoGCL: Rethinking Homophily in Graph Contrastive Learning

Contrastive Cross-scale Graph Knowledge Synergy

Yifei Zhang (The Chinese University of Hong Kong), Yankai Chen (The Chinese University of Hong Kong), Zixing Song (The Chinese University of Hong Kong), Irwin King (The Chinese University of Hong Kong)

Graph Contrastive Learning with Generative Adversarial Network

Cheng Wu (Tsinghua University), Chaokun Wang (Tsinghua University), Jingcao Xu (Tsinghua University), Ziyang Liu (Tsinghua University), Kai Zheng (Kuaishou Inc.), Xiaowei Wang (Kuaishou Inc.), Yang Song (Kuaishou Inc.), Kun Gai (Unaffiliated)

BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs

Zhen Yang (Tsinghua University), Tinglin Huang (Yale University; Yale University), Ming Ding (Tsinghua University), Yuxiao Dong (Tsinghua University), Rex Ying (Yale University ), Yukuo Cen (Tsinghua University), Yangliao Geng (Tsinghua University), Jie Tang (Tsinghua University)

Thursday, August 10, 1:30 PM-3:30 PM, Room 103C, (Robust ML II). Session Chair: Yifeng Gao

How does the Memorization of Neural Networks Impact Adversarial Robust Models?

Han Xu (Michigan State University), Xiaorui Liu (North Carilina State University), Wentao Wang (Michigan State University), Zitao Liu (Jinan University), Anil Jain (Michigan State University), Jiliang Tang (Michigan State University)

Enhance Diffusion to Improve Robust Generalization

Jianhui Sun (University of Virginia), Sanchit Sinha (University of Virginia), Aidong Zhang (University of Virginia)

Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution

Tsuyoshi Ide (IBM Research, Thomas J. Watson Research Center), Naoki Abe (IBM Research, Thomas J. Watson Research Center)

Doubly Robust AUC Optimization against Noisy and Adversarial Samples

Chenkang Zhang (Nanjing University of Information Science and Technology), Wanli Shi (Nanjing University of Information Science and Technology), Lei Luo (Nanjing University of Science and Technology), Bin Gu (Nanjing University of Information Science and Technology; Mohamed bin Zayed University of Artificial Intelligence)

Robust Positive-Unlabeled Learning via Noise Negative Sample Self-Correction

Zhangchi Zhu (East China Normal University), Lu Wang (Microsoft Research), Pu Zhao (Microsoft Research), Chao Du (Microsoft Research), Wei Zhang (East China Normal University), Hang Dong (Microsoft Research), Bo Qiao (Microsoft Research), Qingwei Lin (Microsoft Research), Saravan Rajmohan (Microsoft 365), Dongmei Zhang (Microsoft Research)

Self-Adaptive Perturbation Radii for Adversarial Training

Huimin Wu (Nanjing University of Information Science and Technology), Wanli Shi (Nanjing University of Information Science and Technology), Chenkang Zhang (Nanjing University of Information Science and Technology), Bin Gu (Nanjing University of Information Science and Technology; Mohamed bin Zayed University of Artificial Intelligence)

Thursday, August 10, 1:30 PM-3:30 PM, Room 201A, (KDD for Science and Education). Session Chair: Fan Yang

Learning Behavior-Oriented Knowledge Tracing

Bihan Xu (School of Computer Science and Technology, University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Zhenya Huang (School of Computer Science and Technology, University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Jiayu Liu (School of Data Science, University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Shuanghong Shen (School of Data Science, University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Qi Liu (School of Computer Science and Technology, University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Enhong Chen (Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Jinze Wu (iFLYTEK Research, iFLYTEK Co., Ltd), Shijin Wang (State Key Laboratory of Cognitive Intelligence; iFLYTEK AI Research, iFLYTEK Co., Ltd)

IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics

Jia-Qi Yang (Nanjing University), Yucheng Xu (Nanjing University), Jia-Lei Shen (Nanjing University), Kebin Fan (Nanjing University), De-Chuan Zhan (Nanjing University), Yang Yang (Nanjing University of Science and Technology)

GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing

Hangyu Wang (Shanghai Jiaotong University), Ting Long (Jilin University), Liang Yin (Shanghai Jiaotong University), Weinan Zhang (Shanghai Jiaotong University), Wei Xia (Huawei Noah’s Ark Lab), Qichen Hong (Huawei CBG Edu AI Lab), Dingyin Xia (Huawei CBG Edu AI Lab), Ruiming Tang (Huawei NoahÊäØ Ark Lab), Yong Yu (Shanghai Jiaotong University)

Semi-Supervised Graph Imbalanced Regression

Gang Liu (University of Notre Dame), Tong Zhao (Snap Inc.), Eric Inae (University of Notre Dame), Tengfei Luo (University of Notre Dame), Meng Jiang (University of Notre Dame)

Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers

Yu Zhang (University of Illinois at Urbana-Champaign), Bowen Jin (University of Illinois at Urbana-Champaign), Xiusi Chen (University of California, Los Angeles), Yanzhen Shen (University of Illinois at Urbana-Champaign), Yunyi Zhang (University of Illinois at Urbana-Champaign), Yu Meng (University of Illinois at Urbana-Champaign), Jiawei Han (University of Illinois at Urbana-Champaign)

Meta Multi-Agent Exercise Recommendation: A Game Application Perspective

Fei Liu (Hefei University of Technology), Xuegang Hu (Hefei University of Technology), Shuochen Liu (Hefei University of Technology), Chenyang Bu (Hefei University of Technology), Le Wu (Hefei University of Technology)

Thursday, August 10, 1:30 PM-3:30 PM, Room 201B, (Urban Data II). Session Chair: Yujun Yan

LightPath: Lightweight and Scalable Path Representation Learning

Sean Bin Yang (Aalborg University), Jilin Hu (East China Normal University), Chenjuan Guo (East China Normal University), Bin Yang (East China Normal University), Christian Jensen (Aalborg University)

Urban Region Representation Learning with OpenStreetMap Building Footprints

Yi Li (Nanyang Technological University), Weiming Huang (Nanyang Technological University), Gao Cong (Nanyang Technological University), Hao Wang (Nanyang Technological University), Zheng Wang (Nanyang Technological University)

Multi-Temporal Relationship Inference in Urban Areas

Shuangli Li (University of Science and Technology of China; Baidu Research), Jingbo Zhou (Baidu Research), Ji Liu (Baidu Research), Tong Xu (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligenc), Enhong Chen (University of Science and Technology of China; State Key Laboratory of Cognitive Intelligence), Hui Xiong (The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology)

A Study of Situational Reasoning for Traffic Understanding

Jiarui Zhang (USC/ISI), Filip Ilievski (USC/ISI), Kaixin Ma (CMU), Aravinda Kollaa (USC/ISI), Jonathan Francis (Bosch), Alessandro Oltramari (Bosch)

Frigate: Frugal Spatio-temporal Forecasting on Road Networks

Mridul Gupta (Indian Institute of Technology Delhi), Hariprasad Kodamana (Indian Institute of Technology Delhi), Sayan Ranu (Indian Institute of Technology Delhi)