Abstract
In this paper we explore some aspects of the Hypercircle Inequality (Hi) in the context of kernel-based machine learning. We briefly describe Hi and its potential relevance to kernel- based learning when the data is known exactly and then extend it to circumstances where there is known data error (Hide). © 2011 Universidad de Jaén.
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APA
Khompurngson, K., & Micchelli, C. A. (2011). Hide. Jaen Journal on Approximation, 3(1), 87–115. https://doi.org/10.1145/1037949.1024403
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