data deletion

Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning ICLR 2025 DeRDaVa: Deletion-Robust Data Valuation for Machine Learning AAAI 2024 Fair Machine Unlearning: Data Removal while Mitigating Disparities AISTATS 2024 Machine Unlearning via Null Space Calibration IJCAI 2024 Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable NeurIPS 2024 What makes unlearning hard and what to do about it NeurIPS 2024 Forget Unlearning: Towards True Data-Deletion in Machine Learning ICML 2023 K9db: Privacy-Compliant Storage For Web Applications By Construction OSDI 2023 On the Trade-Off between Actionable Explanations and the Right to be Forgotten ICLR 2023 Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten ICML 2023 Algorithms that Approximate Data Removal: New Results and Limitations NeurIPS 2022 Repairing Neural Networks by Leaving the Right Past Behind NeurIPS 2022 Adaptive Machine Unlearning NeurIPS 2021 Amnesiac Machine Learning AAAI 2021 Approximate Data Deletion from Machine Learning Models AISTATS 2021 Descent-to-Delete: Gradient-Based Methods for Machine Unlearning ALT 2021 Machine Unlearning for Random Forests ICML 2021 Online Forgetting Process for Linear Regression Models AISTATS 2021 Making AI Forget You: Data Deletion in Machine Learning NeurIPS 2019