Cover Image

High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lu, Fred, Curtin, Ryan R., Raff, Edward, Ferraro, Francis, Holt, James
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification
by: Lu, Fred, et al.
Published: (2024)

SparDL: Distributed Deep Learning Training with Efficient Sparse Communication
by: Zhao, Minjun, et al.
Published: (2023)

Scalable High-Dimensional Multivariate Linear Regression for Feature-Distributed Data
by: Huang, Shuo-Chieh, et al.
Published: (2023)

Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient
by: Deng, Xiaoge, et al.
Published: (2021)

DIGEST: Fast and Communication Efficient Decentralized Learning with Local Updates
by: Gholami, Peyman, et al.
Published: (2023)

Towards Efficient and Scalable Distributed Vector Search with RDMA
by: Zhi, Xiangyu, et al.
Published: (2025)

Detection of Global Anomalies on Distributed IoT Edges with Device-to-Device Communication
by: Ochiai, Hideya, et al.
Published: (2024)

Communication-Efficient Federated Group Distributionally Robust Optimization
by: Guo, Zhishuai, et al.
Published: (2024)

SignMuon: Communication-Efficient Distributed Muon Optimization
by: Mishra, Neel, et al.
Published: (2026)

CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning
by: Wang, Mengdi, et al.
Published: (2025)

FedComLoc: Communication-Efficient Distributed Training of Sparse and Quantized Models
by: Yi, Kai, et al.
Published: (2024)

High-Dimensional Sparse Data Low-rank Representation via Accelerated Asynchronous Parallel Stochastic Gradient Descent
by: Hu, Qicong, et al.
Published: (2024)

A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
by: Song, Jiajun, et al.
Published: (2024)

Communication-Efficient Distributed Learning with Local Immediate Error Compensation
by: Cheng, Yifei, et al.
Published: (2024)

Federated LoRA with Sparse Communication
by: Kuo, Kevin, et al.
Published: (2024)

Communication-Efficient Distributed Deep Learning via Federated Dynamic Averaging
by: Theologitis, Michail, et al.
Published: (2024)

TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference
by: Gond, Raja, et al.
Published: (2025)

OpenDiLoCo: An Open-Source Framework for Globally Distributed Low-Communication Training
by: Jaghouar, Sami, et al.
Published: (2024)

An All-Reduce Compatible Top-K Compressor for Communication-Efficient Distributed Learning
by: Chen, Chuyan, et al.
Published: (2025)

Communication-Efficient Distributed Training for Collaborative Flat Optima Recovery in Deep Learning
by: Dimlioglu, Tolga, et al.
Published: (2025)

Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering
by: Liu, Changxin, et al.
Published: (2024)

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning
by: Zhang, Zihan, et al.
Published: (2025)

SDSL-Solver: Scalable Distributed Sparse Linear Solvers for Large-Scale Interior Point Methods
by: Yang, Shaofeng, et al.
Published: (2026)

ScalableHD: Scalable and High-Throughput Hyperdimensional Computing Inference on Multi-Core CPUs
by: Parikh, Dhruv, et al.
Published: (2025)

Hybrid Dual-Batch and Cyclic Progressive Learning for Efficient Distributed Training
by: Lu, Kuan-Wei, et al.
Published: (2025)

FSA: An Alternative Efficient Implementation of Native Sparse Attention Kernel
by: Yan, Ran, et al.
Published: (2025)

Grappa: Gradient-Only Communication for Scalable Graph Neural Network Training
by: Xu, Chongyang, et al.
Published: (2026)

Distributed Generative Inference of LLM at Internet Scales with Multi-Dimensional Communication Optimization
by: Chen, Jiu, et al.
Published: (2026)

ReLATE: Learning Efficient Sparse Encoding for High-Performance Tensor Decomposition
by: Helal, Ahmed E., et al.
Published: (2025)

Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimization
by: Deng, Xiumei, et al.
Published: (2024)

A More Scalable Sparse Dynamic Data Exchange
by: Geyko, Andrew, et al.
Published: (2023)

Preserving Near-Optimal Gradient Sparsification Cost for Scalable Distributed Deep Learning
by: Yoon, Daegun, et al.
Published: (2024)

Parm: Efficient Training of Large Sparsely-Activated Models with Dedicated Schedules
by: Pan, Xinglin, et al.
Published: (2024)

FDC: Fast KV Dimensionality Compression for Efficient LLM Inference
by: Zhang, Zeyu, et al.
Published: (2024)

Communication-Efficient Sparsely-Activated Model Training via Sequence Migration and Token Condensation
by: Chen, Fahao, et al.
Published: (2024)

FSD-Inference: Fully Serverless Distributed Inference with Scalable Cloud Communication
by: Oakley, Joe, et al.
Published: (2024)

Scalable and Cost-Efficient ML Inference: Parallel Batch Processing with Serverless Functions
by: Barrak, Amine, et al.
Published: (2025)

Communication-Efficient Federated Fine-Tuning
by: Theologitis, Michael, et al.
Published: (2025)

Communication Efficient and Provable Federated Unlearning
by: Tao, Youming, et al.
Published: (2024)

Runtime-Orchestrated Second-Order Optimization for Scalable LLM Training
by: Lu, Yishun, et al.
Published: (2026)