epfml / byzantine-robust-noniid-optimizerLinks
☆18Updated 3 years ago
Alternatives and similar repositories for byzantine-robust-noniid-optimizer
Users that are interested in byzantine-robust-noniid-optimizer are comparing it to the libraries listed below
Sorting:
- This repo implements several algorithms for learning with differential privacy.☆111Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 4 years ago
- ☆55Updated 2 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆34Updated 3 years ago
- ☆54Updated 4 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆159Updated 4 years ago
- Official code repository for our accepted work "Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning" in NeurI…☆24Updated last year
- Robust aggregation for federated learning with the RFA algorithm.☆51Updated 3 years ago
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341☆77Updated 2 years ago
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆201Updated 4 years ago
- ☆70Updated 3 years ago
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆22Updated 4 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆38Updated 3 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆147Updated 3 years ago
- Adversarial attacks and defenses against federated learning.☆20Updated 2 years ago
- ☆38Updated 4 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆27Updated 2 years ago
- Papers related to federated learning in top conferences (2020-2024).☆70Updated last year
- Algorithms to recover input data from their gradient signal through a neural network☆309Updated 2 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- Code related to the paper "Machine Unlearning of Features and Labels"☆72Updated last year
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)☆49Updated 3 years ago
- ☆26Updated 3 years ago
- A Fine-grained Differentially Private Federated Learning against Leakage from Gradients☆15Updated 2 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆60Updated 6 years ago
- This is a simple backdoor model for federated learning.We use MNIST as the original data set for data attack and we use CIFAR-10 data set…☆14Updated 5 years ago
- A pytorch implementation of the paper "Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage".☆61Updated 3 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆152Updated 3 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆43Updated 4 years ago