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» On Fitting Mixture Models
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STOC
2004
ACM
145views Algorithms» more  STOC 2004»
14 years 9 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
TCSV
2010
13 years 3 months ago
Video Foreground Detection Based on Symmetric Alpha-Stable Mixture Models
Background subtraction (BS) is an efficient technique for detecting moving objects in video sequences. A simple BS process involves building a model of the background and extractin...
Harish Bhaskar, Lyudmila Mihaylova, Alin Achim
CVPR
2012
IEEE
11 years 11 months ago
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Bolei Zhou, Xiaogang Wang, Xiaoou Tang
CVPR
2005
IEEE
14 years 11 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
CSDA
2007
108views more  CSDA 2007»
13 years 9 months ago
Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
Xiaoning Wang, Alan Schumitzky, David Z. D'Argenio