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Maxiset in sup-norm for kernel estimators。
Sup-norm convergence of the empirical process indexed by functions and applications
Sup-norm convergence the empirical process functions and applications
2009/9/23
A new approximation of the unifonn empirical and
quantile processes results in a weak invariance principle indexed by
functions for the general empirical process. Consequences of this
result are we...
Variable selection for multicategory SVM via adaptive sup-norm regularization
Classification L1-norm penalty multicategory sup-norm SVM
2009/9/16
Support Vector Machine (SVM) is a popular classification paradigm in machine learning and has achieved great success in real applications. However, the standard SVM can not select variables automatica...
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
Linear model Lasso Dantzig Sparsity Model selection Sign consistency
2009/9/16
We derive the l∞ convergence rate simultaneously for Lasso and Dantzig estimators in a high-dimensional linear regression model under a mutual coherence assumption on the Gram matrix of the design and...