340 search results - page 14 / 68 » Linear Dependent Dimensionality Reduction |
131
Voted
ICML
2004
IEEE
15 years 7 months ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
124
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ICML
2005
IEEE
16 years 2 months ago
2005
IEEE
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
122
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SDM
2012
SIAM
13 years 4 months ago
2012
SIAM
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
121
Voted
IJON
1998
15 years 1 months ago
1998
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
102
Voted
MCS
2001
Springer
15 years 6 months ago
2001
Springer
Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many machine learning problems [4, 16]. However, the exten...