A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks

doi:10.1007/s11633-022-1315-6

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	A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks
	Jin Xie; San-Yang Liu; Jia-Xi Chen
发表期刊	Machine Intelligence Research
ISSN	2731-538X
	2022
卷号	19 期号:1 页码:63-74
摘要	This paper aims to propose a framework for manifold regularization (MR) based distributed semi-supervised learning (DSSL) using single layer feed-forward neural network (SLFNN). The proposed framework, denoted as DSSL-SLFNN is based on the SLFNN, MR framework, and distributed optimization strategy. Then, a series of algorithms are derived to solve DSSL problems. In DSSL problems, data consisting of labeled and unlabeled samples are distributed over a communication network, where each node has only access to its own data and can only communicate with its neighbors. In some scenarios, DSSL problems cannot be solved by centralized algorithms. According to the DSSL-SLFNN framework, each node over the communication network exchanges the initial parameters of the SLFNN with the same basis functions for semi-supervised learning (SSL). All nodes calculate the global optimal coefficients of the SLFNN by using distributed datasets and local updates. During the learning process, each node only exchanges local coefficients with its neighbors rather than raw data. It means that DSSL-SLFNN based algorithms work in a fully distributed fashion and are privacy preserving methods. Finally, several simulations are presented to show the efficiency of the proposed framework and the derived algorithms.
关键词	Distributed learning (DL) semi-supervised learning (SSL) manifold regularization (MR) single layer feed-forward neural network (SLFNN) privacy preserving
DOI	10.1007/s11633-022-1315-6
引用统计	被引频次：12[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55928
专题	学术期刊_Machine Intelligence Research
作者单位	School of Mathematics and Statistics, Xidian University, Xi′an 710071, China
推荐引用方式 GB/T 7714	Jin Xie,San-Yang Liu,Jia-Xi Chen. A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks[J]. Machine Intelligence Research,2022,19(1):63-74.
APA	Jin Xie,San-Yang Liu,&Jia-Xi Chen.(2022).A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks.Machine Intelligence Research,19(1),63-74.
MLA	Jin Xie,et al."A Framework for Distributed Semi-supervised Learning Using Single-layer Feedforward Networks".Machine Intelligence Research 19.1(2022):63-74.

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