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View all- Wang JMu KLiu B(2022)Coal Spontaneous Combustion Temperature Prediction Based on Fuzzy Combined Kernel Relevance Vector MachineMathematical Problems in Engineering10.1155/2022/17245062022(1-10)Online publication date: 19-Jul-2022
Incremental Learning Algorithm Based on Relevance Vector Machine
Authors: 
Jun Lei, Yiyue Tao, Xiongye SuAuthors Info & Claims
Pages 225 - 228
Abstract
Aiming at the large memory footprint of traditional vector machine (Relevance Vector Machine, RVM) when processing big data in supervised learning, the idea of incremental learning is introduced into the traditional RVM and the incremental learning of RVM based on sparse model is studied. Method of an incremental learning algorithm of RVM based on sparse model is proposed. The algorithm considers the influence of the existing model and the new sample on the sparse RVM model, and transforms each incremental learning to the problem of solving the maximized edge likelihood function. The sparse RVM model is updated by solving the optimization problem continuously. Simulation results show that this method can effectively reduce the memory space requirements.
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- Incremental Learning Algorithm Based on Relevance Vector Machine
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Published In
June 2018
261 pages
ISBN:9781450364607
DOI:10.1145/3239576
Copyright © 2018 ACM.
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In-Cooperation
- University of Electronic Science and Technology of China: University of Electronic Science and Technology of China
- Southwest Jiaotong University
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 June 2018
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- Research
- Refereed limited
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ICAIP '18
ICAIP '18: 2018 the 2nd International Conference on Advances in Image Processing
June 16 - 18, 2018
Chengdu, China
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View all- Wang JMu KLiu B(2022)Coal Spontaneous Combustion Temperature Prediction Based on Fuzzy Combined Kernel Relevance Vector MachineMathematical Problems in Engineering10.1155/2022/17245062022(1-10)Online publication date: 19-Jul-2022
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