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» Learning Generative Models of Similarity Matrices
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UAI
2003
13 years 5 months ago
Learning Generative Models of Similarity Matrices
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Rómer Rosales, Brendan J. Frey
BMCBI
2010
153views more  BMCBI 2010»
13 years 4 months ago
Metamotifs - a generative model for building families of nucleotide position weight matrices
Background: Development of high-throughput methods for measuring DNA interactions of transcription factors together with computational advances in short motif inference algorithms...
Matias Piipari, Thomas A. Down, Tim J. P. Hubbard
ICML
2009
IEEE
14 years 5 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
LION
2009
Springer
114views Optimization» more  LION 2009»
13 years 11 months ago
Substitution Matrices and Mutual Information Approaches to Modeling Evolution
Abstract. Substitution matrices are at the heart of Bioinformatics: sequence alignment, database search, phylogenetic inference, protein family classication are based on Blosum, P...
Stephan Kitchovitch, Yuedong Song, Richard C. van ...
BMCBI
2008
130views more  BMCBI 2008»
13 years 4 months ago
A novel series of compositionally biased substitution matrices for comparing Plasmodium proteins
Background: The most common substitution matrices currently used (BLOSUM and PAM) are based on protein sequences with average amino acid distributions, thus they do not represent ...
Kevin Brick, Elisabetta Pizzi