Byzantine-resilient distributed SGD with TensorFlow.
☆40Jan 22, 2021Updated 5 years ago
Alternatives and similar repositories for AggregaThor
Users that are interested in AggregaThor are comparing it to the libraries listed below
Sorting:
- ☆16May 10, 2019Updated 6 years ago
- System Support for Byzantine Machine Learning☆10Oct 4, 2021Updated 4 years ago
- Associated codebase for Byzantine-resilient distributed / decentralized machine learning papers from INSPIRE Lab☆15Oct 11, 2021Updated 4 years ago
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Jul 13, 2020Updated 5 years ago
- ☆19Dec 7, 2020Updated 5 years ago
- Pytorch implementation of backdoor unlearning.☆21Jun 8, 2022Updated 3 years ago
- [AAMAS 2025] Privacy-preserving and Personalized RLHF, with convergence guarantees. The Code contains experiments for training multiple i…☆15Apr 16, 2025Updated 10 months ago
- Arbitrary precision integers in TensorFlow☆11Dec 27, 2022Updated 3 years ago
- Official Code Implementation for the CCS 2022 Paper "On the Privacy Risks of Cell-Based NAS Architectures"☆11Nov 21, 2022Updated 3 years ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆65May 22, 2020Updated 5 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆28Jun 29, 2023Updated 2 years ago
- Learning from history for Byzantine Robustness☆26Jun 11, 2021Updated 4 years ago
- ☆55Feb 19, 2023Updated 3 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆152Oct 3, 2022Updated 3 years ago
- ☆28Mar 15, 2023Updated 2 years ago
- ☆14Jun 6, 2023Updated 2 years ago
- ☆17Nov 30, 2022Updated 3 years ago
- Official Implementation of ICML'23 "Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting".☆15Jun 9, 2023Updated 2 years ago
- ☆18Mar 12, 2024Updated last year
- Pytorch implementations of Client-Customized Adaptation for Parameter-Efficient Federated Learning (Findings of ACL: ACL 2023)☆17Oct 9, 2023Updated 2 years ago
- A sybil-resilient distributed learning protocol.☆112Sep 9, 2025Updated 5 months ago
- ☆14Jul 11, 2019Updated 6 years ago
- Implementation of two BFT consensus protocols☆18Dec 13, 2023Updated 2 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆44Oct 29, 2021Updated 4 years ago
- Secure aggregation protocol for TensorFlow Federated☆24Aug 19, 2020Updated 5 years ago
- Code for USENIX Security 2023 Paper "Every Vote Counts: Ranking-Based Training of Federated Learning to Resist Poisoning Attacks"☆21May 19, 2024Updated last year
- 🔥🔥🔥 Detecting hidden backdoors in Large Language Models with only black-box access☆52Jun 2, 2025Updated 9 months ago
- A Parallel Secure Machine Learning Framework on GPUs☆21Nov 17, 2021Updated 4 years ago
- FLTracer: Accurate Poisoning Attack Provenance in Federated Learning☆24Jun 14, 2024Updated last year
- Getting Starting with NIMBUS-CORE☆10Dec 16, 2023Updated 2 years ago
- Code and dataset for the paper: "Can Editing LLMs Inject Harm?"☆21Dec 26, 2025Updated 2 months ago
- ☆24Dec 8, 2024Updated last year
- Official implementation of our work "Collaborative Fairness in Federated Learning."☆55May 28, 2024Updated last year
- Robust aggregation for federated learning with the RFA algorithm.☆53Sep 13, 2022Updated 3 years ago
- Bayesian Nonparametric Federated Learning of Neural Networks☆146May 29, 2019Updated 6 years ago
- ☆26Jan 13, 2020Updated 6 years ago
- Libraries for efficient and scalable group-structured dataset pipelines.☆25Jun 18, 2025Updated 8 months ago
- Byzantine Attack-Resistant Federated Averaging Based on Outlier Elimination☆24Dec 26, 2022Updated 3 years ago
- ☆26Jan 25, 2019Updated 7 years ago