OPTML-Group / Unlearn-Sparse
[NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
☆68Updated last year
Alternatives and similar repositories for Unlearn-Sparse:
Users that are interested in Unlearn-Sparse are comparing it to the libraries listed below
- ☆44Updated 7 months ago
- ☆55Updated 4 years ago
- [ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, …☆23Updated 5 months ago
- Backdoor Safety Tuning (NeurIPS 2023 & 2024 Spotlight)☆25Updated 4 months ago
- Camouflage poisoning via machine unlearning☆17Updated 2 years ago
- ☆12Updated last year
- ☆23Updated 3 years ago
- code release for "Unrolling SGD: Understanding Factors Influencing Machine Unlearning" published at EuroS&P'22☆22Updated 3 years ago
- Code related to the paper "Machine Unlearning of Features and Labels"☆69Updated last year
- ☆85Updated 2 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆48Updated 2 years ago
- Source code for ECCV 2022 Poster: Data-free Backdoor Removal based on Channel Lipschitzness☆30Updated 2 years ago
- ☆34Updated last year
- This is the repository that introduces research topics related to protecting intellectual property (IP) of AI from a data-centric perspec…☆22Updated last year
- Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"☆57Updated last year
- [ICLR2023] Distilling Cognitive Backdoor Patterns within an Image☆34Updated 5 months ago
- ☆18Updated last year
- ☆29Updated 2 years ago
- [USENIX Security 2022] Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture☆16Updated 2 years ago
- Certified Removal from Machine Learning Models☆65Updated 3 years ago
- Methods for removing learned data from neural nets and evaluation of those methods☆34Updated 4 years ago
- Official Implementation of ICLR 2022 paper, ``Adversarial Unlearning of Backdoors via Implicit Hypergradient''☆54Updated 2 years ago
- Official codes for "Understanding Deep Gradient Leakage via Inversion Influence Functions", NeurIPS 2023☆15Updated last year
- "In-Context Unlearning: Language Models as Few Shot Unlearners". Martin Pawelczyk, Seth Neel* and Himabindu Lakkaraju*; ICML 2024.☆24Updated last year
- ☆19Updated 3 months ago
- [ICML 2023] Are Diffusion Models Vulnerable to Membership Inference Attacks?☆34Updated 6 months ago
- Github repo for One-shot Neural Backdoor Erasing via Adversarial Weight Masking (NeurIPS 2022)☆15Updated 2 years ago
- Anti-Backdoor learning (NeurIPS 2021)☆82Updated last year
- Query-Efficient Data-Free Learning from Black-Box Models☆22Updated 2 years ago