This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.
☆63Nov 5, 2018Updated 7 years ago
Alternatives and similar repositories for dpml-benchmark
Users that are interested in dpml-benchmark are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆136Dec 8, 2022Updated 3 years ago
- A implementation of Privacy Buckets: A numerical tool to calculate privacy loss☆11May 19, 2022Updated 4 years ago
- Code for fast dpsgd implementations in JAX/TF☆59Oct 12, 2022Updated 3 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆26May 30, 2019Updated 7 years ago
- ☆38Jun 21, 2022Updated 4 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆78Feb 15, 2024Updated 2 years ago
- Source code for the VLDB 2021 paper.☆11May 19, 2021Updated 5 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆279Dec 5, 2023Updated 2 years ago
- DualQuery: Practical Private Query Release Algorithm☆19Jul 7, 2015Updated 11 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Apr 16, 2021Updated 5 years ago
- Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)☆46Apr 22, 2022Updated 4 years ago
- ☆17Aug 16, 2024Updated last year
- ☆27Dec 15, 2022Updated 3 years ago
- A Privacy Preserving Data Mining Platform☆46Jul 10, 2012Updated 14 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Analytic calibration for differential privacy with Gaussian perturbations☆51Oct 7, 2018Updated 7 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆47Nov 25, 2019Updated 6 years ago
- ☆17May 1, 2022Updated 4 years ago
- Code for NIPS'2017 paper☆51Jul 16, 2020Updated 6 years ago
- Scaleable input gradient regularization☆22Jul 8, 2019Updated 7 years ago
- Privacy Engineering Collaboration Space☆280Aug 18, 2025Updated 11 months ago
- Comparison of gradient estimation techniques for black-box adversarial examples☆11Oct 31, 2018Updated 7 years ago
- A library for running membership inference attacks against ML models☆152Dec 8, 2022Updated 3 years ago
- Library for training machine learning models with privacy for training data☆2,022Jul 8, 2026Updated last month
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- ☆80May 22, 2022Updated 4 years ago
- Implements attacks and defenses for machine learning systems☆13May 7, 2017Updated 9 years ago
- Simulate a federated setting and run differentially private federated learning.☆393Mar 7, 2025Updated last year
- ☆31Jul 10, 2026Updated last month
- ☆66Jul 30, 2019Updated 7 years ago
- Diffprivlib: The IBM Differential Privacy Library☆920Sep 17, 2025Updated 10 months ago
- Code for Auditing DPSGD☆39Feb 15, 2022Updated 4 years ago
- ☆17Sep 9, 2020Updated 5 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆63Jun 16, 2020Updated 6 years ago
- Open source password manager - Proton Pass • AdSecurely store, share, and autofill your credentials with Proton Pass, the end-to-end encrypted password manager trusted by millions.
- TensorFlow World 2019 Tutorial: Privacy-Preserving Machine Learning with TF Encrypted & PySyft☆45May 16, 2023Updated 3 years ago
- Training PyTorch models with differential privacy☆1,949Jul 13, 2026Updated last month
- Code for the paper "Quantifying Privacy Leakage in Graph Embedding" published in MobiQuitous 2020☆18Nov 11, 2021Updated 4 years ago
- Optimized Circuit Generation for Secure Multiparty Computation☆12Nov 25, 2019Updated 6 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆146Jan 22, 2026Updated 6 months ago
- An implementation of Deep Learning with Differential Privacy☆28Mar 25, 2023Updated 3 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Mar 1, 2018Updated 8 years ago