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» The Generalized Dimensionality Reduction Problem
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ICPR
2004
IEEE
15 years 11 months ago
Nearest Neighbor Ensemble
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
Bojun Yan, Carlotta Domeniconi
VISUAL
2005
Springer
15 years 3 months ago
Face Recognition Using Modular Bilinear Discriminant Analysis
We present a Modular Bilinear Disciminant Analysis (MBDA) approach for face recognition. A set of classifiers are trained independently on specific face regions, and different c...
Muriel Visani, Christophe Garcia, Jean-Michel Joli...
NIPS
2007
14 years 11 months ago
Colored Maximum Variance Unfolding
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
PR
2006
89views more  PR 2006»
14 years 9 months ago
Gaussian fields for semi-supervised regression and correspondence learning
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
Jakob J. Verbeek, Nikos A. Vlassis
TOPNOC
2010
14 years 4 months ago
Search-Order Independent State Caching
Abstract. State caching is a memory reduction technique used by model checkers to alleviate the state explosion problem. It has traditionally been coupled with a depth-first search...
Sami Evangelista, Lars Michael Kristensen