kuc2477 / pytorch-splitnet
PyTorch implementation of ICML 2017 paper, SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
☆18Updated 7 years ago
Alternatives and similar repositories for pytorch-splitnet:
Users that are interested in pytorch-splitnet are comparing it to the libraries listed below
- Implementation of Compressed SGD with Compressed Gradients in Pytorch☆12Updated 8 months ago
- vector quantization for stochastic gradient descent.☆33Updated 4 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated 8 months ago
- Federated posterior averaging implemented in JAX☆51Updated last year
- Federated learning with PyTorch (federated averaging and consensus optimization): with 'reduced' bandwidth☆42Updated 10 months ago
- Attentive Federated Learning for Private NLM☆61Updated 8 months ago
- [ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time☆42Updated last year
- Bayesian Nonparametric Federated Learning of Neural Networks☆144Updated 5 years ago
- Code for the signSGD paper☆83Updated 4 years ago
- ☆16Updated last year
- R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]☆35Updated 2 years ago
- Code Implemntion from the article Multi-Armed Bandit Based Client Schedulingfor Federated Learning☆16Updated 4 years ago
- FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)☆25Updated 2 years ago
- Federated Multi-Task Learning☆129Updated 6 years ago
- ☆23Updated last year
- Federated Learning with Partial Model Personalization☆42Updated 2 years ago
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆59Updated 6 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆66Updated 4 years ago
- Code for "Federated Accelerated Stochastic Gradient Descent" (NeurIPS 2020)☆15Updated 3 years ago
- ☆23Updated 3 years ago
- ☆28Updated 2 years ago
- ☆40Updated last year
- Simplicial-FL to manage client device heterogeneity in Federated Learning☆22Updated last year
- [ICML2022] ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training☆21Updated 2 years ago
- Federated Learning Based Dynamic Regularization☆18Updated 3 years ago
- Federated Bilevel Optimization☆16Updated 2 years ago
- ☆27Updated 2 years ago
- Learning rate adaptation for differentially private stochastic gradient descent☆16Updated 3 years ago
- ☆26Updated 2 years ago
- SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847☆31Updated 8 months ago