Complexity control in statistical learning

DOI10.1007/BF02719779zbMath1378.62006OpenAlexW2089195188MaRDI QIDQ2371223

Sameer M. Jalnapurkar

Publication date: 2 July 2007

Published in: Sādhanā (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02719779

zbMATH Keywords

learning theorycomplexity controlregularisation covering number

Mathematics Subject Classification ID

Uses Software

• ElemStatLearn

Cites Work

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• Best choices for regularization parameters in learning theory: on the bias-variance problem.
• Rates of uniform convergence of empirical means with mixing processes
• Information criteria for selecting possibly misspecified parametric models
• Regularization networks and support vector machines
• Learning theory estimates via integral operators and their approximations
• On the mathematical foundations of learning
• Model Selection and Multimodel Inference
• The elements of statistical learning. Data mining, inference, and prediction

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