epfml / error-feedback-SGD
SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847
☆31Updated 7 months ago
Alternatives and similar repositories for error-feedback-SGD:
Users that are interested in error-feedback-SGD are comparing it to the libraries listed below
- Code for the signSGD paper☆83Updated 4 years ago
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆59Updated 6 years ago
- vector quantization for stochastic gradient descent.☆33Updated 4 years ago
- Atomo: Communication-efficient Learning via Atomic Sparsification☆25Updated 6 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆66Updated 4 years ago
- ☆74Updated 5 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated 7 months ago
- FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)☆25Updated last year
- Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"☆31Updated 4 years ago
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆75Updated 3 years ago
- ☆46Updated 5 years ago
- R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]☆34Updated 2 years ago
- Implementation of (overlap) local SGD in Pytorch☆33Updated 4 years ago
- FedNAS: Federated Deep Learning via Neural Architecture Search☆54Updated 3 years ago
- Implementation of Compressed SGD with Compressed Gradients in Pytorch☆12Updated 7 months ago
- QSGD-TF☆21Updated 5 years ago
- Code for "Adaptive Gradient Quantization for Data-Parallel SGD", published in NeurIPS 2020.☆30Updated 4 years ago
- [ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time☆42Updated last year
- ☆28Updated 5 years ago
- Code for "Federated Accelerated Stochastic Gradient Descent" (NeurIPS 2020)☆15Updated 3 years ago
- Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…☆90Updated 2 years ago
- Understanding Top-k Sparsification in Distributed Deep Learning☆24Updated 5 years ago
- Algorithm: Decentralized Parallel Stochastic Gradient Descent☆41Updated 6 years ago
- PyTorch implementation of ICML 2017 paper, SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Paral…☆18Updated 7 years ago
- Adaptive gradient sparsification for efficient federated learning: an online learning approach☆18Updated 4 years ago
- Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?☆14Updated 2 years ago
- Federated posterior averaging implemented in JAX☆51Updated last year
- Simple Hierarchical Count Sketch in Python☆20Updated 3 years ago
- Bayesian Nonparametric Federated Learning of Neural Networks☆144Updated 5 years ago
- Federated Learning Based Dynamic Regularization☆18Updated 3 years ago