Caponnetto, Andrea - Department of Mathematics, City University of Hong Kong

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Caponnetto, Andrea - Department of Mathematics, City University of Hong Kong

Are Loss Functions All the Same? A. Caponnetto
Journal of Machine Learning Research () Submitted 12/04; Published Learning from Examples as an Inverse Problem
Dipartimento di Informatica e Scienze dell'Informazione
Fast rates for regularized least-squares algorithm Andrea Caponnetto a
Risk bounds for regularized least-squares algorithm with operator-valued kernels
Empirical Effective Dimension and Optimal Rates for Regularized Least Squares Algorithm
SOME PROPERTIES OF EMPIRICAL RISK MINIMIZATION OVER DONSKER ANDREA CAPONNETTO AND ALEXANDER RAKHLIN
Optimal rates for regularization operators in learning theory
Adaptation for regularization operators in learning theory
ON EARLY STOPPING IN GRADIENT DESCENT LEARNING YUAN YAO, LORENZO ROSASCO, AND ANDREA CAPONNETTO
Cross-validation based Adaptation for Regularization Operators in Learning
Journal of Machine Learning Research (XXXX) Submitted XX; Published XXX Universal Kernels for Multi-Task Learning
RISK BOUNDS FOR RANDOM REGRESSION GRAPHS A. CAPONNETTO AND S. SMALE
Journal of Machine Learning Research 1 (2000) 1-48 Submitted 4/00; Published 10/00 Stability Properties of Empirical Risk Minimization over
Journal of Machine Learning Research 5 (2004) 13631390 Submitted 12/03; Revised 7/04; Published 10/04 Some Properties of Regularized Kernel Methods
MODEL SELECTION FOR REGULARIZED LEAST-SQUARES ALGORITHM IN LEARNING THEORY
November 10, 2007 Derived Distance
Computer Science and Artificial Intelligence Laboratory Technical Report
OPTIMAL RATES FOR REGULARIZED LEAST-SQUARES A. CAPONNETTO AND E. DE VITO
April 4, 2008 On a model of visual cortex: learning invariance and selectivity
A NOTE ON THE ROLE OF SQUARED LOSS IN REGRESSION ANDREA CAPONNETTO
A note on stability of error bounds in statistical learning Ming Li, Department of Mathematics, City University of Hong Kong, 83 Tat Chee
ENTROPY CONDITIONS FOR Lr-CONVERGENCE OF EMPIRICAL PROCESSES
Learning, Regularization and Ill-Posed Inverse Lorenzo Rosasco
Support Vectors Algorithms as Regularization Andrea Caponnetto1,2