Tabrizian / learning-to-quantizeLinks
Code for "Adaptive Gradient Quantization for Data-Parallel SGD", published in NeurIPS 2020.
☆30Updated 4 years ago
Alternatives and similar repositories for learning-to-quantize
Users that are interested in learning-to-quantize are comparing it to the libraries listed below
Sorting:
- vector quantization for stochastic gradient descent.☆35Updated 5 years ago
- Code for the signSGD paper☆88Updated 4 years ago
- Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"☆31Updated 4 years ago
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆59Updated 6 years ago
- [ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training☆223Updated last year
- ☆46Updated 5 years ago
- SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847☆31Updated last year
- FedNAS: Federated Deep Learning via Neural Architecture Search☆54Updated 4 years ago
- ☆131Updated last year
- Model compression by constrained optimization, using the Learning-Compression (LC) algorithm☆72Updated 3 years ago
- Implementation of (overlap) local SGD in Pytorch☆33Updated 5 years ago
- Atomo: Communication-efficient Learning via Atomic Sparsification☆27Updated 6 years ago
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆108Updated 6 years ago
- Understanding Top-k Sparsification in Distributed Deep Learning☆24Updated 5 years ago
- ☆33Updated 5 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆71Updated 4 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆91Updated 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
- ☆22Updated 2 years ago
- Pytorch-based early exit network inspired by branchynet☆34Updated 2 months ago
- Implementation of Compressed SGD with Compressed Gradients in Pytorch☆13Updated last year
- GRACE - GRAdient ComprEssion for distributed deep learning☆139Updated last year
- LotteryFL: Empower Edge Intelligence with Personalized and Communication-Efficient Federated Learning (2021 IEEE/ACM Symposium on Edge Co…☆41Updated 2 years ago
- Federated Dynamic Sparse Training☆30Updated 3 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- Algorithm: Decentralized Parallel Stochastic Gradient Descent☆45Updated 6 years ago
- [ICLR-2020] Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers.☆31Updated 5 years ago
- ☆75Updated 6 years ago
- Sketched SGD☆28Updated 5 years ago
- Prune DNN using Alternating Direction Method of Multipliers (ADMM)☆98Updated 5 years ago