chentianyi1991 / LAG-code
LAG code for NeurIPS 2018
☆9Updated 6 years ago
Alternatives and similar repositories for LAG-code
Users that are interested in LAG-code are comparing it to the libraries listed below
Sorting:
- Code of NeurIPS 2019 paper: Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients☆16Updated 5 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆22Updated 4 years ago
- Code for paper "Byzantine-Resilient Distributed Finite-Sum Optimization over Networks"☆18Updated 4 years ago
- ☆18Updated 4 years ago
- ☆16Updated 6 years ago
- Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).☆13Updated 4 years ago
- Federated Learning on XGBoost☆46Updated 5 years ago
- FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning☆17Updated 2 years ago
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 2 years ago
- A list of papers using/about Federated Learning especially malicious client and attacks.☆12Updated 4 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated 9 months ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆63Updated 4 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆45Updated 2 years ago
- ☆19Updated 3 years ago
- Differentially Private Federated Learning: A Client Level Perspective☆12Updated 5 years ago
- Official implementation of our work "Collaborative Fairness in Federated Learning."☆51Updated 11 months ago
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Updated 4 years ago
- Supporting code for https://arxiv.org/abs/2010.00753.☆19Updated 3 years ago
- Asynchronous Federated Learning☆19Updated 3 years ago
- Federated learning with PyTorch (federated averaging and consensus optimization): with 'reduced' bandwidth☆42Updated last year
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆68Updated 4 years ago
- Code for paper "Byzantine-Resilient Decentralized Stochastic Optimization with Robust Aggregation Rules"☆18Updated last year
- SCAFFOLD and FedAvg implementation☆60Updated 3 years ago
- ☆19Updated last year
- ☆94Updated 3 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated last year
- Attentive Federated Learning for Private NLM☆61Updated 9 months ago
- ☆24Updated 5 years ago
- Chain-PPFL: A Privacy-Preserving Federated Learning Framework based on Chained SMC☆34Updated 4 years ago