Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment.
IEEE Signal Processing Magazine(2013)
摘要
Over the last decade, nonlinear kernel-based learning methods have been widely used in the sciences and in industry for solving, e.g., classification, regression, and ranking problems. While their users are more than happy with the performance of this powerful technology, there is an emerging need to additionally gain better understanding of both the learning machine and the data analysis problem ...
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关键词
Machine learning,Learning systems,Kernel,Nonlinear estimation,Complexity theory,Data analysis,Signal processing algorithms
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