DOIAbstract
AbstractWe survey a number of recent results concerning the behaviour of algorithms for learning classifiers based on the solution of a regularized least-squares problem
AbstractWe survey a number of recent results concerning the behaviour of algorithms for learning classifiers based on the solution of a regularized least-squares problem
Abstract. We provide sample complexity of the problem of learning halfspaces with monotonic noise, u...
This is a collection of information about regularized least squares (RLS). The facts here are not ne...
We develop a theoretical analysis of generalization performances of regularized least-squares on rep...
We survey a number of recent results concerning the behaviour of algorithms for learning classifiers...
AbstractWe survey a number of recent results concerning the behaviour of algorithms for learning cla...
Abstract—The regularized least-squares classification is one of the most promising alternatives to s...
We investigate the problem of model selection for learning algorithms depending on a continuous para...
We consider the solution of binary classification problems via Tikhonov regularization in a Reprodu...
Over the past decades, regularization theory is widely applied in various areas of machine learning ...
Over the past decades, regularization theory is widely applied in various areas of machine learning ...
We develop a theoretical analysis of the generalization perfor- mances of regularized least-squares ...
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Compute...
In this work we present the first efficient algorithm for unsupervised training of multi-class re...
We develop a theoretical analysis of the generalization perfor-mances of regularized least-squares a...
We revisit the classical technique of regularised least squares (RLS) for nonlinear classification i...
Abstract. We provide sample complexity of the problem of learning halfspaces with monotonic noise, u...
This is a collection of information about regularized least squares (RLS). The facts here are not ne...
We develop a theoretical analysis of generalization performances of regularized least-squares on rep...
We survey a number of recent results concerning the behaviour of algorithms for learning classifiers...
AbstractWe survey a number of recent results concerning the behaviour of algorithms for learning cla...
Abstract—The regularized least-squares classification is one of the most promising alternatives to s...
We investigate the problem of model selection for learning algorithms depending on a continuous para...
We consider the solution of binary classification problems via Tikhonov regularization in a Reprodu...
Over the past decades, regularization theory is widely applied in various areas of machine learning ...
Over the past decades, regularization theory is widely applied in various areas of machine learning ...
We develop a theoretical analysis of the generalization perfor- mances of regularized least-squares ...
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Compute...
In this work we present the first efficient algorithm for unsupervised training of multi-class re...
We develop a theoretical analysis of the generalization perfor-mances of regularized least-squares a...
We revisit the classical technique of regularised least squares (RLS) for nonlinear classification i...
Abstract. We provide sample complexity of the problem of learning halfspaces with monotonic noise, u...
This is a collection of information about regularized least squares (RLS). The facts here are not ne...
We develop a theoretical analysis of generalization performances of regularized least-squares on rep...
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