The regularized least squares algorithm and the problem of learning halfspaces

DOI10.1016/j.ipl.2011.01.011zbMath1260.68189OpenAlexW1987010876MaRDI QIDQ1944907

Ha Quang Minh

Publication date: 28 March 2013

Published in: Information Processing Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ipl.2011.01.011

zbMATH Keywords

computational complexitycomputational learning theoryanalysis of algorithmskernelhalfspacesregularized least squares algorithm

Mathematics Subject Classification ID

Computational learning theory (68Q32) Analysis of algorithms and problem complexity (68Q25) Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.) (68Q17)

Cites Work

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• Learning intersections and thresholds of halfspaces
• An upper bound on the sample complexity of PAC-learning halfspaces with respect to the uniform distribution
• Halfspace learning, linear programming, and nonmalicious distributions
• Optimal aggregation of classifiers in statistical learning.
• Optimum bounds for the distributions of martingales in Banach spaces
• Learning theory estimates via integral operators and their approximations
• On early stopping in gradient descent learning
• On the mathematical foundations of learning
• Efficient noise-tolerant learning from statistical queries
• Agnostically Learning Halfspaces
• Theory of Reproducing Kernels
• Some properties of Gaussian reproducing kernel Hilbert spaces and their implications for function approximation and learning theory

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