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SDM
2010
SIAM
168views Data Mining» more  SDM 2010»
14 years 8 months ago
Convex Principal Feature Selection
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, J...
TIT
2010
130views Education» more  TIT 2010»
14 years 4 months ago
The power of convex relaxation: near-optimal matrix completion
This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a gr...
Emmanuel J. Candès, Terence Tao
ESA
2007
Springer
101views Algorithms» more  ESA 2007»
15 years 4 months ago
Linear Data Structures for Fast Ray-Shooting Amidst Convex Polyhedra
We consider the problem of ray shooting in a three-dimensional scene consisting of k (possibly intersecting) convex polyhedra with a total of n facets. That is, we want to preproc...
Haim Kaplan, Natan Rubin, Micha Sharir
ICML
2009
IEEE
15 years 11 months ago
Learning kernels from indefinite similarities
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
Yihua Chen, Maya R. Gupta, Benjamin Recht
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ICML
2006
IEEE
15 years 11 months ago
Discriminative unsupervised learning of structured predictors
We present a new unsupervised algorithm for training structured predictors that is discriminative, convex, and avoids the use of EM. The idea is to formulate an unsupervised versi...
Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dal...