csong27 / auditing-text-generationLinks
Code for Auditing Data Provenance in Text-Generation Models (in KDD 2019)
☆10Updated 6 years ago
Alternatives and similar repositories for auditing-text-generation
Users that are interested in auditing-text-generation are comparing it to the libraries listed below
Sorting:
- This repo implements several algorithms for learning with differential privacy.☆111Updated 3 years ago
- ☆32Updated last year
- Code for Auditing DPSGD☆37Updated 3 years ago
- ☆46Updated 6 years ago
- ☆77Updated 3 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆67Updated 4 years ago
- ☆19Updated 2 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- ☆22Updated 3 years ago
- ☆15Updated last year
- A codebase that makes differentially private training of transformers easy.☆181Updated 3 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆132Updated last year
- Code for ML Doctor☆92Updated last year
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆60Updated 6 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆36Updated 3 years ago
- Code related to the paper "Machine Unlearning of Features and Labels"☆72Updated last year
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆67Updated last year
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆56Updated 6 years ago
- ☆80Updated 3 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆201Updated 8 years ago
- ☆31Updated 4 years ago
- ☆12Updated 4 years ago
- ☆26Updated 4 years ago
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Updated 4 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆86Updated 4 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆75Updated last year
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆46Updated 6 years ago
- Public implementation of ICML'19 paper "White-box vs Black-box: Bayes Optimal Strategies for Membership Inference"☆18Updated 5 years ago
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)☆50Updated 3 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆39Updated 6 years ago