Two Birds With One Stone: Toward Communication and Computation Efficient Federated Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2024.3421955
Abstract: Federated learning (FL) is a distributed machine learning paradigm proposed to ensure user data privacy. However, in practical scenarios, terminal devices often contend for limited network resources, making communication overhead a significant obstacle to its… read more here.
Keywords: two birds; birds one; federated learning; communication overhead ... See more keywords
Differentially Private Malicious Agent Avoidance in Multiagent Advising Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2019.2906574
Abstract: Agent advising is one of the key approaches to improve agent learning performance by enabling agents to ask for advice between each other. Existing agent advising approaches have two limitations. The first limitation is that… read more here.
Keywords: agent; communication overhead; approach; agent advising ... See more keywords
A Topology Optimization Method for Reducing Communication Overhead in the Kalman Consensus Filter
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11157107
Abstract: Distributed estimation and tracking of interested objects over wireless sensor networks (WSNs) is a hot research topic. Since network topology possesses distinctive structural parameters and plays an important role for the performance of distributed estimation,… read more here.
Keywords: communication; optimization method; communication overhead; topology ... See more keywords