gdisag / gradient_disaggregation
☆14Updated last year
Alternatives and similar repositories for gradient_disaggregation:
Users that are interested in gradient_disaggregation are comparing it to the libraries listed below
- Learning from history for Byzantine Robustness☆22Updated 3 years ago
- ☆31Updated 4 years ago
- ☆13Updated last year
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆44Updated last year
- A list of papers using/about Federated Learning especially malicious client and attacks.☆12Updated 4 years ago
- Simplicial-FL to manage client device heterogeneity in Federated Learning☆22Updated last year
- Adversarial attacks and defenses against federated learning.☆15Updated last year
- ☆54Updated 3 years ago
- ☆38Updated 3 years ago
- ☆12Updated 3 years ago
- Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)☆43Updated last year
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆30Updated 2 years ago
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆20Updated 3 years ago
- ☆15Updated 5 years ago
- ☆54Updated last year
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 2 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆39Updated 3 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 5 years ago
- Official code repository for our accepted work "Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning" in NeurI…☆22Updated 4 months ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆71Updated 3 years ago
- ☆40Updated last year
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 3 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated 6 months ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated last year
- reveal the vulnerabilities of SplitNN☆30Updated 2 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆33Updated 4 months ago
- Robust aggregation for federated learning with the RFA algorithm.☆47Updated 2 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆30Updated 2 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 6 years ago