dhroth / sketchedsgdLinks
Sketched SGD
☆28Updated 5 years ago
Alternatives and similar repositories for sketchedsgd
Users that are interested in sketchedsgd are comparing it to the libraries listed below
Sorting:
- Code for the signSGD paper☆92Updated 4 years ago
- Simple Hierarchical Count Sketch in Python☆21Updated 4 years ago
- Stochastic Gradient Push for Distributed Deep Learning☆170Updated 2 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆74Updated 5 years ago
- Atomo: Communication-efficient Learning via Atomic Sparsification☆28Updated 7 years ago
- ☆77Updated 6 years ago
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆58Updated 7 years ago
- DRACO: Byzantine-resilient Distributed Training via Redundant Gradients☆23Updated 7 years ago
- Practical low-rank gradient compression for distributed optimization: https://arxiv.org/abs/1905.13727☆149Updated last year
- ☆46Updated 5 years ago
- Implementation of (overlap) local SGD in Pytorch☆34Updated 5 years ago
- A compressed adaptive optimizer for training large-scale deep learning models using PyTorch☆26Updated 6 years ago
- InstaHide: Instance-hiding Schemes for Private Distributed Learning☆50Updated 5 years ago
- FedNAS: Federated Deep Learning via Neural Architecture Search☆54Updated 4 years ago
- R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]☆37Updated 2 years ago
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆78Updated 4 years ago
- [ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training☆225Updated last year
- GRACE - GRAdient ComprEssion for distributed deep learning☆139Updated last year
- Algorithm: Decentralized Parallel Stochastic Gradient Descent☆47Updated 7 years ago
- ☆27Updated 3 years ago
- vector quantization for stochastic gradient descent.☆35Updated 5 years ago
- Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"☆31Updated 5 years ago
- Federated posterior averaging implemented in JAX☆52Updated 2 years ago
- Simplicial-FL to manage client device heterogeneity in Federated Learning☆22Updated 2 years ago
- FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)☆26Updated 2 years ago
- Federated Learning Framework Benchmark (UniFed)☆49Updated 2 years ago
- Implementation of Parameter Server using PyTorch communication lib☆43Updated 6 years ago
- SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847☆32Updated last year
- A PyTorch implementation of the paper "Decoupled Parallel Backpropagation with Convergence Guarantee"☆29Updated 7 years ago
- ☆80Updated 3 years ago