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:
- Code for Auditing DPSGD☆37Updated 3 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- ☆45Updated 5 years ago
- This repo implements several algorithms for learning with differential privacy.☆109Updated 2 years ago
- ☆32Updated last year
- ☆75Updated 3 years ago
- ☆19Updated 2 years ago
- ☆21Updated 3 years ago
- A codebase that makes differentially private training of transformers easy.☆176Updated 2 years ago
- Code for ML Doctor☆90Updated last year
- Code for the paper: Label-Only Membership Inference Attacks☆66Updated 4 years ago
- Code related to the paper "Machine Unlearning of Features and Labels"☆71Updated last year
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆127Updated last year
- ☆26Updated 3 years ago
- ☆80Updated 3 years ago
- ☆15Updated last year
- ☆24Updated 3 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆74Updated last year
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)☆49Updated 3 years ago
- ☆10Updated 3 years ago
- ☆12Updated 4 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆64Updated last year
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆54Updated 6 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆39Updated 6 years ago
- ☆11Updated 4 years ago
- ☆26Updated 6 years ago
- ☆30Updated 4 years ago
- ☆19Updated last year
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆38Updated 3 years ago
- Public implementation of the paper "On the Importance of Difficulty Calibration in Membership Inference Attacks".☆16Updated 3 years ago