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» Regression-based latent factor models
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CSDA
2011
14 years 8 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
16 years 1 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»
15 years 24 days 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»
15 years 1 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 5 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