Work

Adaptive Top-K in SGD for Communication-Efficient Distributed Learning in Multi-Robot Collaboration

Year: 2024

Type: article

Source: IEEE Journal of Selected Topics in Signal Processing

DOI: 10.1109/jstsp.2024.3381373

Authors: Mengzhe Ruan, Guangfeng Yan, Yuanzhang Xiao, Linqi Song, Weitao Xu

Institutions: City University of Hong Kong, City University of Hong Kong, Shenzhen Research Institute, University of Hawaiʻi at Mānoa, University of Hawaii System

Language: English

Topic: Stochastic Gradient Optimization Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: City University of Hong Kong, National Natural Science Foundation of China, Shenzhen Research Institute, City University of Hong Kong, Government of Shandong Province

Awards: G4386184646, G5516222651, G7981627932

OpenAlex ID: W4394002425

FWCI: 0.737

Cites: 44

Cited by: 5

Related to: 10