One-pass-throw-away learning of temporal class-shift by multi-stratum network
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Title One-pass-throw-away learning of temporal class-shift by multi-stratum network
Creator Mongkhon Thakong
Contributor Suphakant Phimoltares, Chidchanok Lursinsap
Publisher Chulalongkorn University
Publication Year 2558
Keyword Streaming technology (Telecommunications), Online data processing, เทคโนโลยีสตรีมมิง ‪(โทรคมนาคม)‬, การประมวลผลข้อมูลแบบออนไลน์
Abstract The problem of learning streaming non-expired and temporally expired data occurring in various business applications was studied. If there exists a class whose all data are eventually expired with some unknown reasons, then the relevant neurons and their links must be entirely removed. A new learning based on dynamic network structure called Multi-Stratum Network Learning (MSNL) was proposed to cope with this problem of data life change. Furthermore, to speed up the learning time and to maintain a minimum space complexity for streaming data, the new concept of one-pass-throw-away learning in forms of recursive functions for handling the expiration class was introduced. The experimental results signified that the proposed algorithm outperformed the other incremental-like learning algorithms in terms of time and space complexities.
URL Website cuir.car.chula.ac.th
Chulalongkorn University

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