TheSalon / fast-dpsgd
Code for fast dpsgd implementations in JAX/TF
☆59Updated 2 years ago
Alternatives and similar repositories for fast-dpsgd:
Users that are interested in fast-dpsgd are comparing it to the libraries listed below
- Github pages backend for https://differentialprivacy.org☆25Updated 8 months ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆93Updated 8 months ago
- Tilted Empirical Risk Minimization (ICLR '21)☆59Updated last year
- ☆80Updated 2 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆52Updated 4 years ago
- The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size☆17Updated 5 years ago
- Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"☆104Updated 4 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"☆27Updated 2 years ago
- Code for Auditing DPSGD☆37Updated 3 years ago
- [NeurIPS 2020] Simple and practical private mean and covariance estimation.☆34Updated 4 years ago
- Computationally friendly hyper-parameter search with DP-SGD☆24Updated last month
- ☆156Updated 2 years ago
- ☆18Updated 2 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- Federated posterior averaging implemented in JAX☆51Updated last year
- Differentially Private Optimization for PyTorch 👁🙅♀️☆184Updated 4 years ago
- ☆36Updated 2 years ago
- InstaHide: Instance-hiding Schemes for Private Distributed Learning☆50Updated 4 years ago
- Neural network verification in JAX☆141Updated last year
- Hessian spectral density estimation in TF and Jax☆121Updated 4 years ago
- DeepOBS: A Deep Learning Optimizer Benchmark Suite☆103Updated last year
- Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy☆17Updated 4 months ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆59Updated 4 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆80Updated 6 months ago
- Source code for "Neural Anisotropy Directions"☆15Updated 4 years ago
- Sketched SGD☆28Updated 4 years ago
- Convolutional Neural Tangent Kernel☆109Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 3 years ago
- A concise primer on Differential Privacy☆28Updated 4 years ago