nikikilbertus / blind-justice
Blind Justice Code for the paper "Blind Justice: Fairness with Encrypted Sensitive Attributes", ICML 2018
☆14Updated 5 years ago
Alternatives and similar repositories for blind-justice:
Users that are interested in blind-justice are comparing it to the libraries listed below
- Code and data for the experiments in "On Fairness and Calibration"☆50Updated 2 years ago
- ☆26Updated 7 years ago
- A python library to discover and mitigate biases in machine learning models and datasets☆19Updated last year
- ☆13Updated 4 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- ☆32Updated 7 years ago
- Python code for implementing embeddings in the Wasserstein space of elliptical distributions☆11Updated 4 years ago
- Code accompanying our paper at AISTATS 2020☆21Updated 4 years ago
- Code for "Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?"☆44Updated last year
- Comparing fairness-aware machine learning techniques.☆160Updated 2 years ago
- Implementation of provably Rawlsian fair ML algorithms for contextual bandits.☆14Updated 7 years ago
- Code/figures in Right for the Right Reasons☆55Updated 4 years ago
- ☆17Updated 4 years ago
- ☆50Updated last year
- References for Papers at the Intersection of Causality and Fairness☆18Updated 6 years ago
- Implementation of Adversarial Debiasing in PyTorch to address Gender Bias☆30Updated 4 years ago
- ☆42Updated 6 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]☆51Updated 4 years ago
- ☆18Updated 3 years ago
- Implementation of the estimator for combining noisy observations from Dawid and Skene (1979)☆38Updated 10 years ago
- ☆22Updated 5 years ago
- Achieve error-rate fairness between societal groups for any score-based classifier.☆16Updated 9 months ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated last year
- ☆14Updated 10 months ago
- An implementation of Wasserstein Fair Classification, a conference paper submitted to UAI 2019.☆21Updated 5 years ago
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆30Updated 3 years ago
- ☆20Updated 5 years ago
- IPython notebook with synthetic experiments for AFLite, based on the ICML 2020 paper, "Adversarial Filters of Dataset Biases".☆16Updated 4 years ago
- Code for "Imitation Attacks and Defenses for Black-box Machine Translations Systems"☆36Updated 4 years ago