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» Regression-based latent factor models
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CSDA
2011
14 years 4 months ago
Hierarchical multilinear models for multiway data
Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as produc...
Peter D. Hoff
WWW
2008
ACM
15 years 10 months ago
Social and semantics analysis via non-negative matrix factorization
Social media such as Web forum often have dense interactions between user and content where network models are often appropriate for analysis. Joint non-negative matrix factorizat...
Zhi-Li Wu, Chi-Wa Cheng, Chun-hung Li
NECO
1998
116views more  NECO 1998»
14 years 9 months ago
GTM: The Generative Topographic Mapping
Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example ...
Christopher M. Bishop, Markus Svensén, Chri...
CSDA
2008
154views more  CSDA 2008»
14 years 9 months ago
Independent factor discriminant analysis
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...
Angela Montanari, Daniela G. Calò, Cinzia V...
SIGIR
1999
ACM
15 years 1 months ago
Probabilistic Latent Semantic Indexing
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fit...
Thomas Hofmann