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Active Online Learning in the Binary Perceptron Problem

文献类型：期刊论文

作者Zhou, HJ
刊名COMMUNICATIONS IN THEORETICAL PHYSICS
出版日期2019
卷号71期号:2页码:243-252
关键词STATISTICAL-MECHANICS EXAMPLES INFERENCE ALGORITHM NETWORKS STORAGE
ISSN号0253-6102
DOI10.1088/0253-6102/71/2/243
英文摘要The binary perceptron is the simplest artificial neural network formed by N input units and one output unit, with the neural states and the synaptic weights all restricted to +/- 1 values. The task in the teacher-student scenario is to infer the hidden weight vector by training on a set of labeled patterns. Previous efforts on the passive learning mode have shown that learning from independent random patterns is quite inefficient. Here we consider the active online learning mode in which the student designs every new Ising training pattern. We demonstrate that it is mathematically possible to achieve perfect (error-free) inference using only N designed training patterns, but this is computationally unfeasible for large systems. We then investigate two Bayesian statistical designing protocols, which require 2.3N and 1.9N training patterns, respectively, to achieve error-free inference. If the training patterns are instead designed through deductive reasoning, perfect inference is achieved using N+log(2)N samples. The performance gap between Bayesian and deductive designing strategies may be shortened in future work by taking into account the possibility of ergodicity breaking in the version space of the binary perceptron.
学科主题Physics
语种英语
源URL[http://ir.itp.ac.cn/handle/311006/23497]  
专题理论物理研究所_理论物理所1978-2010年知识产出
计算平台成果
作者单位1.Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Zhou, HJ. Active Online Learning in the Binary Perceptron Problem[J]. COMMUNICATIONS IN THEORETICAL PHYSICS,2019,71(2):243-252.
APA Zhou, HJ.(2019).Active Online Learning in the Binary Perceptron Problem.COMMUNICATIONS IN THEORETICAL PHYSICS,71(2),243-252.
MLA Zhou, HJ."Active Online Learning in the Binary Perceptron Problem".COMMUNICATIONS IN THEORETICAL PHYSICS 71.2(2019):243-252.

入库方式： OAI收割

来源：理论物理研究所

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