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104
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ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
JMLR
2008
14 years 9 months ago
2008
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
SIAMCOMP
2000
14 years 9 months ago
2000
Abstract. We consider two natural generalizations of the notion of transversal to a finite hypergraph, arising in data-mining and machine learning, the so called multiple and parti...
112
Voted
KDD
2008
ACM
15 years 10 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
ICML
2005
IEEE
15 years 10 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...