Downloads provided by UsageCountsOnline One-Class Machines Based On The Coherence Criterion
Noumir, Zineb; Honeine, Paul; Richard, Cédric;
Online One-Class Machines Based On The Coherence Criterion
In this paper, we investigate a novel online one-class classification method. We consider a least-squares optimization problem, where the model complexity is controlled by the coherence criterion as a sparsification rule. This criterion is coupled with a simple updating rule for online learning, which yields a low computational demanding algorithm. Experiments conducted on time series illustrate the relevance of our approach to existing methods.
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France
Optimization, cybersecurity, online one-class machines, optimisation, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, low computational demanding algorithm, online learning, Time series analysis, least squares approximations, one-class, support vector machines, kernel methods, pattern classification, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, adaptive filtering, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, coherence parameter, sparsity, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], one-class classification, least-squares optimization problem, Kernel, machine learning, Dictionaries, learning (artificial intelligence), online one-class classification method, Signal processing algorithms, Coherence, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Optimization, cybersecurity, online one-class machines, optimisation, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, low computational demanding algorithm, online learning, Time series analysis, least squares approximations, one-class, support vector machines, kernel methods, pattern classification, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, adaptive filtering, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, coherence parameter, sparsity, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], one-class classification, least-squares optimization problem, Kernel, machine learning, Dictionaries, learning (artificial intelligence), online one-class classification method, Signal processing algorithms, Coherence, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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