xinyandai / gradient-quantizationLinks
vector quantization for stochastic gradient descent.
☆35Updated 5 years ago
Alternatives and similar repositories for gradient-quantization
Users that are interested in gradient-quantization are comparing it to the libraries listed below
Sorting:
- Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"☆31Updated 4 years ago
- ☆33Updated 5 years ago
- ☆22Updated 4 years ago
- Code for the signSGD paper☆88Updated 4 years ago
- Understanding Top-k Sparsification in Distributed Deep Learning☆24Updated 5 years ago
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆58Updated 6 years ago
- Implementation of Compressed SGD with Compressed Gradients in Pytorch☆13Updated 11 months ago
- SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847☆30Updated 11 months ago
- FedNAS: Federated Deep Learning via Neural Architecture Search☆55Updated 3 years ago
- LotteryFL: Empower Edge Intelligence with Personalized and Communication-Efficient Federated Learning (2021 IEEE/ACM Symposium on Edge Co…☆41Updated 2 years ago
- It is implementation of Research paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING". Deep g…☆18Updated 5 years ago
- Federated Dynamic Sparse Training☆30Updated 3 years ago
- Attentive Federated Learning for Private NLM☆61Updated 11 months ago
- Salvaging Federated Learning by Local Adaptation☆56Updated 11 months ago
- Bayesian Nonparametric Federated Learning of Neural Networks☆143Updated 6 years ago
- Adaptive gradient sparsification for efficient federated learning: an online learning approach☆18Updated 4 years ago
- SCAFFOLD and FedAvg implementation☆59Updated 3 years ago
- [ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time☆44Updated 2 years ago
- Implementation of (overlap) local SGD in Pytorch☆33Updated 4 years ago
- FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)☆26Updated 2 years ago
- Atomo: Communication-efficient Learning via Atomic Sparsification☆27Updated 6 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆84Updated 5 years ago
- This is the code repository for the following paper: "Model pruning enables efficient federated learning on edge devices".☆91Updated 3 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆70Updated 4 years ago
- Code for "Adaptive Gradient Quantization for Data-Parallel SGD", published in NeurIPS 2020.☆30Updated 4 years ago
- Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?☆14Updated 3 years ago
- [ICML2022] ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training☆22Updated 2 years ago
- This repository implements FEDL using pytorch☆55Updated 4 years ago
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆77Updated 3 years ago
- tf implementation of federated learning☆42Updated 6 years ago