December 2024, Volume 26, Issue 2
- Blockchain for Large Language Model Security and Safety: A Holistic Survey [1]
- Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges [21]
- Exploring Large Language Models for Feature Selection: A Data-centric Perspective [44]
- Causal inference under limited outcome observability: A case study with Pinterest Conversion Lift [54]
- DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models [60]
- FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models [76]
- Graph Fairness via Authentic Counterfactuals: Tackling Structural and Causal Challenges. [89]
- FG-SMOTE: Towards Fair Node Classification with Graph Neural Network. [99]
- Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities [109]
June 2024, Volume 26, Issue 1
- Higher-Order Networks Representation and Learning: A Survey [1]
- Synthetic data for learning-based knowledge discovery [19]
- The Case for Hybrid Multi-Objective Optimisation in High-Stakes Machine Learning Applications [24]
- Fairness in Large Language Models: A Taxonomic Survey [34]
- Analyzing and explaining privacy risks on time series data: ongoing work and challenges [49]
December 2023, Volume 25, Issue 2
- An interview with Dr. Jure Lesvek, Winner of ACM SIGKDD 2023 Innovation Award [1]
- Marginal Nodes Matter: Towards Structure Fairness in Graphs [4]
- Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text? [14]
- Storage Systems: Organization, Performance, Coding, Reliability, and Their Data Processing, 1st Edition, October 13, 2021 [22]
- Report on the 3rd International Workshop on Learning to Quantify (LQ 2023) [25]
- Anomaly Detection using Generative Adversarial Networks [29]
- Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs [42]
June 2023, Volume 25, Issue 1
- Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective [1]
- The Need for Unsupervised Outlier Model Selection: A Review and Evaluation of Internal Evaluation Strategies. [19]
- Stop Using the Elbow Criterion for k-means, and How to Choose the Number of Clusters Instead. [36]
- Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking. [43]
- Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey. [54]
- Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising. [73]
December 2022, Volume 24, Issue 2
- An interview with Dr. Huan Liu, Winner of ACM SIGKDD 2022 Innovation Award [1]
- An interview with Dr. Charu Aggarwal, Winner of ACM SIGKDD 2022 Service Award [3]
- Evaluating the Predictive Performance of Positive-Unlabelled Classifiers: a brief critical review and practical recommendations for improvement [5]
- Open challenges for Machine Learning based Early Decision-Making research [12]
- Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications [32]
- Finding Multidimensional Simpson’s Paradox [48]
- Data Augmentation for Deep Graph Learning: A Survey [61]
- KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond [78]
- Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges [81]
- Investigating thresholding techniques in a real predictive maintenance scenario [86]
- Feature Selection for Fault Detection and Prediction based on Event Log Analysis [96]
- Acoustic Structural Integrity Assessment of Ceramics using Supervised Machine Learning and Uncertainty-Based Rejection [105]
- Experiences with Contrastive Predictive Coding in Industrial Time-Series Classification [114]
- Supply Chain Link Prediction on Uncertain Knowledge Graph [124]
