sunjunaimer / LAQLinks
Code of NeurIPS 2019 paper: Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
☆16Updated 5 years ago
Alternatives and similar repositories for LAQ
Users that are interested in LAQ are comparing it to the libraries listed below
Sorting:
- ☆96Updated 4 years ago
- FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.☆193Updated 9 months ago
- Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)☆166Updated 3 years ago
- Accenture Labs Federated Learning☆106Updated last year
- ☆33Updated 3 years ago
- Decentralized federated learning of deep neural networks on non-iid data☆45Updated 3 years ago
- FedMD: Heterogenous Federated Learning via Model Distillation☆161Updated 4 years ago
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆133Updated 2 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆46Updated 3 years ago
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints☆185Updated 4 years ago
- Releasing the source code Version1.☆179Updated 4 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆86Updated 5 years ago
- On the Convergence of FedAvg on Non-IID Data☆275Updated 3 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- Codebase for An Efficient Framework for Clustered Federated Learning.☆121Updated 5 years ago
- diaoenmao / HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients☆179Updated 2 years ago
- PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.☆122Updated 3 years ago
- Fair Resource Allocation in Federated Learning (ICLR '20)☆254Updated 2 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆39Updated last year
- Differentially Private Federated Learning on Heterogeneous Data☆72Updated 3 years ago
- [ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"☆84Updated 3 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆152Updated 3 years ago
- The code in order to implement FedProx (ICPP 2020)☆29Updated 5 years ago
- Study of data imbalance and asynchronous aggregation algorithm on Federated Learning system (using PySyft)☆63Updated 2 years ago
- FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution☆40Updated 3 years ago
- ☆54Updated 4 years ago
- Active Client Selection for Federated Learning☆49Updated 2 years ago
- Code for paper "Byzantine-Resilient Distributed Finite-Sum Optimization over Networks"☆18Updated 5 years ago
- ☆84Updated 4 years ago
- Official implementation of our work "Collaborative Fairness in Federated Learning."☆54Updated last year