Permutational Rademacher Complexity

DOI10.1007/978-3-319-24486-0_14zbMath1471.68226arXiv1505.02910OpenAlexW2594727590MaRDI QIDQ2835630

Ilya Tolstikhin, Gilles Blanchard, Nikita Zhivotovskiy

Publication date: 30 November 2016

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1505.02910

zbMATH Keywords

empirical processesstatistical learning theoryconcentration inequalitiesRademacher complexitytransductive learning

Mathematics Subject Classification ID

Computational learning theory (68Q32) Inequalities; stochastic orderings (60E15) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Measuring distributional asymmetry with Wasserstein distance and Rademacher symmetrization ⋮ Simple and fast algorithm for binary integer and online linear programming

Cites Work

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• Oracle inequalities in empirical risk minimization and sparse recovery problems. École d'Été de Probabilités de Saint-Flour XXXVIII-2008.
• Weak convergence and empirical processes. With applications to statistics
• Local Rademacher complexities
• Concentration Inequalities
• Theory of Classification: a Survey of Some Recent Advances
• Transductive Rademacher Complexity and its Applications
• The best constants in the Khintchine inequality
• 10.1162/153244303321897690
• Learning Theory and Kernel Machines

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