FedComLoc: Communication-Efficient Distributed Training of Sparse and Quantized Models
Fuente:
arXiv
Saved in:
| Main Authors: | Yi, Kai, Meinhardt, Georg, Condat, Laurent, Richtárik, Peter |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression
by: Condat, Laurent, et al.
Published: (2024)
by: Condat, Laurent, et al.
Published: (2024)
Correlated Quantization for Faster Nonconvex Distributed Optimization
by: Panferov, Andrei, et al.
Published: (2024)
by: Panferov, Andrei, et al.
Published: (2024)
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction
by: Demidovich, Yury, et al.
Published: (2024)
by: Demidovich, Yury, et al.
Published: (2024)
MAST: Model-Agnostic Sparsified Training
by: Demidovich, Yury, et al.
Published: (2023)
by: Demidovich, Yury, et al.
Published: (2023)
PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning
by: Wang, Yisu, et al.
Published: (2025)
by: Wang, Yisu, et al.
Published: (2025)
DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling
by: Gao, Yubo, et al.
Published: (2025)
by: Gao, Yubo, et al.
Published: (2025)
AB-Training: A Communication-Efficient Approach for Distributed Low-Rank Learning
by: Coquelin, Daniel, et al.
Published: (2024)
by: Coquelin, Daniel, et al.
Published: (2024)
Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm
by: Elbakary, Ahmed, et al.
Published: (2024)
by: Elbakary, Ahmed, et al.
Published: (2024)
Galvatron: An Automatic Distributed System for Efficient Foundation Model Training
by: Liu, Xinyi, et al.
Published: (2025)
by: Liu, Xinyi, et al.
Published: (2025)
SpaFL: Communication-Efficient Federated Learning with Sparse Models and Low computational Overhead
by: Kim, Minsu, et al.
Published: (2024)
by: Kim, Minsu, et al.
Published: (2024)
Communication Efficient Distributed Training with Distributed Lion
by: Liu, Bo, et al.
Published: (2024)
by: Liu, Bo, et al.
Published: (2024)
FedTrans: Efficient Federated Learning via Multi-Model Transformation
by: Zhu, Yuxuan, et al.
Published: (2024)
by: Zhu, Yuxuan, et al.
Published: (2024)
Distributed Low-Communication Training with Decoupled Momentum Optimization
by: Nedelkoski, Sasho, et al.
Published: (2025)
by: Nedelkoski, Sasho, et al.
Published: (2025)
Byzantine-Robust and Communication-Efficient Distributed Training: Compressive and Cyclic Gradient Coding
by: Li, Chengxi, et al.
Published: (2026)
by: Li, Chengxi, et al.
Published: (2026)
FedCore: Straggler-Free Federated Learning with Distributed Coresets
by: Guo, Hongpeng, et al.
Published: (2024)
by: Guo, Hongpeng, et al.
Published: (2024)
FedFa: A Fully Asynchronous Training Paradigm for Federated Learning
by: Xu, Haotian, et al.
Published: (2024)
by: Xu, Haotian, et al.
Published: (2024)
TrainVerify: Equivalence-Based Verification for Distributed LLM Training
by: Lu, Yunchi, et al.
Published: (2025)
by: Lu, Yunchi, et al.
Published: (2025)
ModTrans: Translating Real-world Models for Distributed Training Simulator
by: Lyu, Yi
Published: (2026)
by: Lyu, Yi
Published: (2026)
FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data
by: AbouNassar, Eman M., et al.
Published: (2026)
by: AbouNassar, Eman M., et al.
Published: (2026)
CompressedScaffnew: The First Theoretical Double Acceleration of Communication from Local Training and Compression in Distributed Optimization
by: Condat, Laurent, et al.
Published: (2022)
by: Condat, Laurent, et al.
Published: (2022)
PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training
by: Ockerman, Seth, et al.
Published: (2025)
by: Ockerman, Seth, et al.
Published: (2025)
Efficient Asynchronous Federated Learning with Sparsification and Quantization
by: Jia, Juncheng, et al.
Published: (2023)
by: Jia, Juncheng, et al.
Published: (2023)
ATTENTION2D: Communication Efficient Distributed Self-Attention Mechanism
by: Elango, Venmugil
Published: (2025)
by: Elango, Venmugil
Published: (2025)
Sparse Training for Federated Learning with Regularized Error Correction
by: Greidi, Ran, et al.
Published: (2023)
by: Greidi, Ran, et al.
Published: (2023)
NestQuant: Post-Training Integer-Nesting Quantization for On-Device DNN
by: Xie, Jianhang, et al.
Published: (2025)
by: Xie, Jianhang, et al.
Published: (2025)
SFPrompt: Communication-Efficient Split Federated Fine-Tuning for Large Pre-Trained Models over Resource-Limited Devices
by: Cao, Linxiao, et al.
Published: (2024)
by: Cao, Linxiao, et al.
Published: (2024)
SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework
by: Zhang, Yuxin, et al.
Published: (2024)
by: Zhang, Yuxin, et al.
Published: (2024)
SparDL: Distributed Deep Learning Training with Efficient Sparse Communication
by: Zhao, Minjun, et al.
Published: (2023)
by: Zhao, Minjun, et al.
Published: (2023)
Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE
by: Firoz, Jesun, et al.
Published: (2025)
by: Firoz, Jesun, et al.
Published: (2025)
FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
by: Abbasi, Ali, et al.
Published: (2024)
by: Abbasi, Ali, et al.
Published: (2024)
EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models
by: Cheng, Jialiang, et al.
Published: (2024)
by: Cheng, Jialiang, et al.
Published: (2024)
Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization
by: Zhu, Zhanda, et al.
Published: (2025)
by: Zhu, Zhanda, et al.
Published: (2025)
Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer
by: Yao, Jinghan, et al.
Published: (2024)
by: Yao, Jinghan, et al.
Published: (2024)
FedAT: Federated Adversarial Training for Distributed Insider Threat Detection
by: Gayathri, R G, et al.
Published: (2024)
by: Gayathri, R G, et al.
Published: (2024)
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences
by: Malinovsky, Grigory, et al.
Published: (2023)
by: Malinovsky, Grigory, et al.
Published: (2023)
FedFT: Improving Communication Performance for Federated Learning with Frequency Space Transformation
by: Palihawadana, Chamath, et al.
Published: (2024)
by: Palihawadana, Chamath, et al.
Published: (2024)
SparseRL-Sync: Lossless Weight Synchronization with ~100x Less Communication
by: Hu, Lucas, et al.
Published: (2026)
by: Hu, Lucas, et al.
Published: (2026)
Enhancing Communication Efficiency in FL with Adaptive Gradient Quantization and Communication Frequency Optimization
by: Tariq, Asadullah, et al.
Published: (2025)
by: Tariq, Asadullah, et al.
Published: (2025)
SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning
by: Ohib, Riyasat, et al.
Published: (2024)
by: Ohib, Riyasat, et al.
Published: (2024)
LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging
by: Maziane, Yassine, et al.
Published: (2026)
by: Maziane, Yassine, et al.
Published: (2026)
Similar Items
-
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression
by: Condat, Laurent, et al.
Published: (2024) -
Correlated Quantization for Faster Nonconvex Distributed Optimization
by: Panferov, Andrei, et al.
Published: (2024) -
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction
by: Demidovich, Yury, et al.
Published: (2024) -
MAST: Model-Agnostic Sparsified Training
by: Demidovich, Yury, et al.
Published: (2023) -
PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning
by: Wang, Yisu, et al.
Published: (2025)