{"total":14,"rows":[{"id":"2306.03819","title":"LEACE: Perfect linear concept erasure in closed form","created":"2023-06-06","cited_by_count":267,"area":null},{"id":"2207.07068","title":"Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey","created":"2022-07-14","cited_by_count":125,"area":null},{"id":"2201.12091","title":"Linear Adversarial Concept Erasure","created":"2022-01-28","cited_by_count":101,"area":null},{"id":"2201.12191","title":"Kernelized Concept Erasure","created":"2022-01-28","cited_by_count":48,"area":null},{"id":"2404.09454","title":"Utility-Fairness Trade-Offs and How to Find Them","created":"2024-04-15","cited_by_count":15,"area":null},{"id":"2408.02464","title":"Fairness and Bias Mitigation in Computer Vision: A Survey","created":"2024-08-05","cited_by_count":13,"area":null},{"id":"2109.03386","title":"On Characterizing the Trade-off in Invariant Representation Learning","created":"2021-09-08","cited_by_count":12,"area":null},{"id":"2109.05535","title":"Adversarial Representation Learning With Closed-Form Solvers","created":"2021-09-12","cited_by_count":2,"area":null},{"id":"2208.02482","title":"Privacy Safe Representation Learning via Frequency Filtering Encoder","created":"2022-08-04","cited_by_count":1,"area":null},{"id":"2502.11031","title":"A Critical Review of Predominant Bias in Neural Networks","created":"2025-02-16","cited_by_count":0,"area":null},{"id":"2507.09031","title":"Confounder-Free Continual Learning via Recursive Feature Normalization","created":"2025-07-11","cited_by_count":0,"area":null},{"id":"2507.10194","title":"Learning Private Representations through Entropy-based Adversarial Training","created":"2025-07-14","cited_by_count":0,"area":null},{"id":"2605.08343","title":"Private Vertical Federated Inference for Time-Series","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2608.25930","title":"Controlling for Omitted Variable Bias in Deep Neural Networks","created":"2026-08-26","cited_by_count":0,"area":null}],"next_cursor":null}