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ICML
2009
IEEE
16 years 7 months ago
Partially supervised feature selection with regularized linear models
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
Thibault Helleputte, Pierre Dupont
ICML
2007
IEEE
16 years 7 months ago
Dimensionality reduction and generalization
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
Sofia Mosci, Lorenzo Rosasco, Alessandro Verri
ICML
2007
IEEE
16 years 7 months ago
Constructing basis functions from directed graphs for value function approximation
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Jeffrey Johns, Sridhar Mahadevan
ICML
2008
IEEE
16 years 7 months ago
Manifold alignment using Procrustes analysis
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
Chang Wang, Sridhar Mahadevan
ICML
2003
IEEE
16 years 7 months ago
Online Feature Selection using Grafting
In the standard feature selection problem, we are given a fixed set of candidate features for use in a learning problem, and must select a subset that will be used to train a mode...
Simon Perkins, James Theiler