Alternatives and similar repositories for survey-deep-gradient-compression

Users that are interested in survey-deep-gradient-compression are comparing it to the libraries listed below

• SamuelGong / Pisces
  [ACM SoCC'22] Pisces: Efficient Federated Learning via Guided Asynchronous Training
  ☆13Updated 8 months ago
• PKU-Chengxu / FLASH
  ☆47Updated 3 years ago
• SymbioticLab / Oort
  Oort: Efficient Federated Learning via Guided Participant Selection
  ☆131Updated 4 years ago
• hclhkbu / GaussianK-SGD
  Understanding Top-k Sparsification in Distributed Deep Learning
  ☆24Updated 6 years ago
• South-hw / FedPara_ICLR22
  ☆12Updated last year
• HKBU-HPML / OMGS-SGD
  Layer-wise Sparsification of Distributed Deep Learning
  ☆10Updated 5 years ago
• amitport / EDEN-Distributed-Mean-Estimation
  This repository is the official implementation of 'EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Lea…
  ☆14Updated 3 years ago
• ParCIS / Ok-Topk
  Ok-Topk is a scheme for distributed training with sparse gradients. Ok-Topk integrates a novel sparse allreduce algorithm (less than 6k c…
  ☆27Updated 3 years ago
• kiddyboots216 / CommEfficient
  PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms
  ☆78Updated 4 years ago
• AI-secure / FLBenchmark-toolkit
  Federated Learning Framework Benchmark (UniFed)
  ☆49Updated 2 years ago
• xinyandai / gradient-quantization
  vector quantization for stochastic gradient descent.
  ☆35Updated 5 years ago
• lusinlu / deep-gradient-compression
  Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"
  ☆31Updated 5 years ago
• kevinhsieh / non_iid_dml
  ☆30Updated 5 years ago
• AdamWei-boop / Federated-Learning-with-Model-Quantization
  Federated learning with model quantization
  ☆16Updated 4 years ago
• bibikar / feddst
  Federated Dynamic Sparse Training
  ☆32Updated 3 years ago
• NiuChaoyue / Secure-Federated-Submodel-Learning
  ☆15Updated 4 years ago
• kimihe / Octo
  Create tiny ML systems for on-device learning.
  ☆20Updated 4 years ago
• kimihe / Falcon
  A computation-parallel deep learning architecture.
  ☆13Updated 6 years ago
• synxlin / deep-gradient-compression
  [ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
  ☆225Updated last year
• BHui97 / PrivateFL
  ☆46Updated 2 years ago
• jaemin-shin / FedBalancer
  ☆30Updated 2 years ago
• vineeths96 / Gradient-Compression
  We present a set of all-reduce compatible gradient compression algorithms which significantly reduce the communication overhead while mai…
  ☆10Updated 4 years ago
• jiangyuang / ModelPruningLibrary
  ☆22Updated 4 years ago
• JYWa / MATCHA
  Communication-efficient decentralized SGD (Pytorch)
  ☆25Updated 5 years ago
• hui-po-wang / ProgFed
  [ICML2022] ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
  ☆22Updated 3 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆57Updated 2 years ago
• scottjiao / Gradient-Compression-Methods
  ☆33Updated 6 years ago
• morningD / FlexCFL
  FlexCFL: A clustered federated learning framework based on TF2.0. Support frameworks: FlexCFL, FedGroup, FedAvg, IFCA, FeSEM, et al.
  ☆54Updated 3 years ago
• yusx-swapp / SPATL
  SPATL: Salient Prameter Aggregation and Transfer Learning for Heterogeneous Federated Learning
  ☆23Updated 3 years ago
• jiangyuang / PruneFL
  This is the code repository for the following paper: "Model pruning enables efficient federated learning on edge devices".
  ☆96Updated 3 years ago