2013
NeurIPS
NeurIPS 2013
Adaptivity to Local Smoothness and Dimension in Kernel Regression
Abstract
We present the first result for kernel regression where the procedure adapts locally at a point $x$ to both the unknown local dimension of the metric and the unknown H\{o}lder-continuity of the regression function at $x$. The result holds with high probability simultaneously at all points $x$ in a metric space of unknown structure."
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Interdisciplinary Bridge
- Artificial Intelligence and Mathematics & Optimization
Authors
Topics
Machine Learning > Core Methods > Regression
Machine Learning > Optimization & Theory > Learning Theory
Machine Learning > Optimization & Theory > Statistical Learning
Mathematics & Optimization > Optimization > Continuous Optimization
Machine Learning > Optimization & Theory > Statistics
Machine Learning > Core Methods > Kernel Methods
Mathematics & Optimization > Optimization > Kernel Methods