PAC-Bayesian bounds for the Gram matrix and least squares regression with a random design

PAC-Bayesian model averaging

D. A. McAllester · 1999

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PAC-Bayesian generalization error bounds for gaussian process classification

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M. Seeger · 2002

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PAC-Bayesian stochastic model selection

D. A. McAllester · 2003

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Simplified PAC-Bayesian margin bounds

D. A. McAllester · 2003

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Aggregated estimators and empirical complexity for least square regression

J.-Y. Audibert · 2004

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Convex Optimization

S. Boyd and L. Vandengerghe · 2004

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Statistical Learning Theory and Stochastic Optimization, Lectures on Probability Theory and Statistics, École d’Été de Probabilités de Saint-Flour XXXI – 2001

O. Catoni · 2004

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PAC-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning

O. Catoni · 2007

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Iterative feature selection in least square regression estimation

P. Alquier · 2008

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PAC-bayesian bounds for randomized empirical risk minimizers

P. Alquier · 2008

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Linear regression through PAC-bayesian truncation

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J.-Y. Audibert and O. Catoni · 2011

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Robust linear least squares regression

J.-Y. Audibert and O. Catoni · 2011

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Supplement to “robust linear least squares regression.”

J.-Y. Audibert and O. Catoni · 2011

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Challenging the empirical mean and empirical variance: a deviation study

O. Catoni · 2012

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Pac-bayes bounds for supervised classification

O. Catoni · 2015

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Generalization bounds for random samples in Hilbert spaces

I. Giulini · 2015

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Robust dimension-free gram operator estimates

Original

I. Giulini · 2015

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Bounding the smallest singular value of a random matrix without concentration

V. Koltchinskii and S. Mendelson · 2015

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Performance of empirical risk minimization in linear aggregation

G. Lecué and S. Mendelson · 2015

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