Alternatives and similar repositories for Count-Sketch-Optimizers

Users that are interested in Count-Sketch-Optimizers are comparing it to the libraries listed below

• dhroth / sketchedsgd
  Sketched SGD
  ☆28Updated 4 years ago
• jiaweizzhao / signSGD-with-Majority-Vote
  ☆74Updated 5 years ago
• nikitaivkin / csh
  Simple Hierarchical Count Sketch in Python
  ☆20Updated 4 years ago
• JYWa / Overlap_Local_SGD
  Implementation of (overlap) local SGD in Pytorch
  ☆33Updated 4 years ago
• epfml / sparsifiedSGD
  Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599
  ☆58Updated 6 years ago
• slowbull / DDG
  A PyTorch implementation of the paper "Decoupled Parallel Backpropagation with Convergence Guarantee"
  ☆29Updated 6 years ago
• eugenium / DGL
  ☆30Updated 4 years ago
• wenwei202 / smoothout
  SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning
  ☆23Updated 6 years ago
• epfml / LocalSGD-Code
  ☆46Updated 5 years ago
• epfml / cola
  CoLa - Decentralized Linear Learning: https://arxiv.org/abs/1808.04883
  ☆20Updated 3 years ago
• hwang595 / ps_pytorch
  implement distributed machine learning with Pytorch + OpenMPI
  ☆51Updated 6 years ago
• jxbz / signSGD
  Code for the signSGD paper
  ☆86Updated 4 years ago
• liamcli / darts_asha
  Code release to reproduce ASHA experiments from "Random Search and Reproducibility for NAS."
  ☆22Updated 5 years ago
• epfml / powersgd
  Practical low-rank gradient compression for distributed optimization: https://arxiv.org/abs/1905.13727
  ☆146Updated 7 months ago
• zhuchen03 / VIBNet
  Compressing Neural Networks using the Variational Information Bottleneck
  ☆66Updated 2 years ago
• justincosentino / robust-sparse-networks
  The Search for Sparse, Robustness Neural Networks
  ☆11Updated 2 years ago
• epfml / error-feedback-SGD
  SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847
  ☆30Updated 10 months ago
• alshedivat / fedpa
  Federated posterior averaging implemented in JAX
  ☆51Updated 2 years ago
• hwang595 / ATOMO
  Atomo: Communication-efficient Learning via Atomic Sparsification
  ☆27Updated 6 years ago
• kudkudak / dnn_sharpest_directions
  Code for "On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length", ICLR 2019
  ☆11Updated 2 years ago
• stevenygd / SWALP
  Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
  ☆62Updated 6 years ago
• kilianFatras / variance_reduced_neural_networks
  Implementation of SVRG and SAGA optimization algorithms for deep learning topics.
  ☆72Updated 4 years ago
• hwang595 / Draco
  DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
  ☆23Updated 6 years ago
• amirgholami / HessianFlow
  ☆83Updated 5 years ago
• oval-group / dfw
  Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch
  ☆62Updated 4 years ago
• fKunstner / fast-individual-gradients-with-autodiff
  ☆26Updated 6 years ago
• facebookresearch / stochastic_gradient_push
  Stochastic Gradient Push for Distributed Deep Learning
  ☆168Updated 2 years ago
• sjmikler / snip-pruning
  SNIP: SINGLE-SHOT NETWORK PRUNING
  ☆31Updated 2 months ago
• kuc2477 / pytorch-splitnet
  PyTorch implementation of ICML 2017 paper, SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Paral…
  ☆17Updated 7 years ago
• wendazhou / nnet-compression-generalization
  ☆27Updated 6 years ago