Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enforces privacy by clipping and sanitising the gradients with Gaussian noise during training.
☆44Apr 12, 2024Updated 2 years ago
Alternatives and similar repositories for dpsgd-optimizer
Users that are interested in dpsgd-optimizer are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆34Apr 29, 2021Updated 5 years ago
- This repo implements several algorithms for learning with differential privacy.☆110Dec 15, 2022Updated 3 years ago
- ☆20Jun 15, 2022Updated 4 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Apr 29, 2021Updated 5 years ago
- Unified, Simplified, Tight and Fast Privacy Amplification in the Shuffle Model of Differential Privacy☆11Oct 27, 2024Updated last year
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- ☆27Dec 15, 2022Updated 3 years ago
- Improved DP-SGD for optimizing☆20Mar 23, 2019Updated 7 years ago
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Oct 26, 2021Updated 4 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆35Feb 8, 2021Updated 5 years ago
- Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions☆16Sep 18, 2020Updated 5 years ago
- OLIVE: Oblivious and Differentially Private Federated Learning on TEE☆17May 10, 2023Updated 3 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Apr 16, 2021Updated 5 years ago
- Exploiting Label Skew in Federated Learning with Model Concatenation (AAAI 2024)☆13Dec 16, 2023Updated 2 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Mar 1, 2018Updated 8 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- ☆18Feb 7, 2024Updated 2 years ago
- Implementation of dp-based federated learning framework using PyTorch☆321Jan 3, 2026Updated 5 months ago
- Naive implementation of basic Differential-Privacy framework and algorithms☆49Aug 30, 2022Updated 3 years ago
- Training PyTorch models with differential privacy☆1,935Jun 14, 2026Updated 2 weeks ago
- We provide a friendly foundational platform for beginners who intend to start Federated Learning (FL)☆20May 26, 2025Updated last year
- Federated Learning Experiments for Remote Sensing image data using convolution neural networks☆17Aug 5, 2021Updated 4 years ago
- ☆12Sep 17, 2019Updated 6 years ago
- ☆10Oct 18, 2021Updated 4 years ago
- Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy☆18Oct 9, 2024Updated last year
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Differentially-private transformers using HuggingFace and Opacus☆149Aug 28, 2024Updated last year
- Implementation of Compressed SGD with Compressed Gradients in Pytorch☆13Jul 25, 2024Updated last year
- A Differentially-Private Random Decision Forest using Smooth Sensitivity☆11Oct 26, 2016Updated 9 years ago
- Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shak…☆423Oct 26, 2024Updated last year
- This is a recommended paper list for the course of Privacy Computing.☆10Mar 26, 2024Updated 2 years ago
- ☆17May 10, 2020Updated 6 years ago
- Code for the WWW21 paper "Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy"☆12Feb 15, 2021Updated 5 years ago
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆32Mar 30, 2022Updated 4 years ago
- Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).☆13Apr 16, 2021Updated 5 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Simulate a federated setting and run differentially private federated learning.☆391Mar 7, 2025Updated last year
- Python implementation of differential privacy using Laplace mechanism☆11Apr 13, 2026Updated 2 months ago
- A Julia implementation of the Paillier partially homomorphic encryption system☆13Oct 8, 2020Updated 5 years ago
- The pytorch implementation of the SAFE model presented in NAACL-Findings-2022☆17Mar 10, 2023Updated 3 years ago
- Code for ICLR'24 Paper "Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks"☆10Mar 12, 2024Updated 2 years ago
- Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing☆17Jan 12, 2022Updated 4 years ago
- Gradient-Leakage Resilient Federated Learning☆14Jul 25, 2022Updated 3 years ago