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NIPS
1997
13 years 8 months ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
ECCC
2007
99views more  ECCC 2007»
13 years 7 months ago
An Exponential Time/Space Speedup For Resolution
Satisfiability algorithms have become one of the most practical and successful approaches for solving a variety of real-world problems, including hardware verification, experime...
Philipp Hertel, Toniann Pitassi
CVPR
2008
IEEE
14 years 9 months ago
Fast image search for learned metrics
We introduce a method that enables scalable image search for learned metrics. Given pairwise similarity and dissimilarity constraints between some images, we learn a Mahalanobis d...
Prateek Jain, Brian Kulis, Kristen Grauman
JMLR
2008
117views more  JMLR 2008»
13 years 7 months ago
Closed Sets for Labeled Data
Closed sets have been proven successful in the context of compacted data representation for association rule learning. However, their use is mainly descriptive, dealing only with ...
Gemma C. Garriga, Petra Kralj, Nada Lavrac
COLT
1998
Springer
13 years 11 months ago
Large Margin Classification Using the Perceptron Algorithm
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...
Yoav Freund, Robert E. Schapire