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» Hierarchical mixture models: a probabilistic analysis
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STOC
2004
ACM
145views Algorithms» more  STOC 2004»
14 years 8 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
ECCV
2010
Springer
14 years 24 days ago
Stacked Hierarchical Labeling
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
NIPS
2004
13 years 9 months ago
Hierarchical Distributed Representations for Statistical Language Modeling
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...
CVPR
2010
IEEE
14 years 3 months ago
Clustering Dynamic Textures with the Hierarchical EM Algorithm
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model ...
Antoni Chan, Emanuele Coviello, Gert Lanckriet
ECWEB
2006
Springer
126views ECommerce» more  ECWEB 2006»
13 years 11 months ago
Web User Segmentation Based on a Mixture of Factor Analyzers
Abstract. This paper proposes an approach for Web user segmentation and online behavior analysis based on a mixture of factor analyzers (MFA). In our proposed framework, we model u...
Yanzan Zhou, Bamshad Mobasher