June 2024, Volume 26, Issue 1

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]

Read More

December 2023, Volume 25, Issue 2

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]

Read More

June 2023, Volume 25, Issue 1

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]

Read More

December 2022, Volume 24, Issue 2

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]

Read More

June 2022, Volume 24, Issue 1

June 2022, Volume 24, Issue 1

  • The Need for Interpretable Features: Motivation and Taxonomy [1]
  • Text Style Transfer: A Review and Experimental Evaluation [14]
  • Report on the Malawi Data Science Bootcamp 2021 [46]
  • Report on the 1st International Workshop on Learning to Quantify (LQ 2021) [49]
  • Diversity and Inclusion Activities in EGC – A 2022 Report [52]

Read More