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» Using mixture models for collaborative filtering
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ICML
2004
IEEE
14 years 5 months ago
The multiple multiplicative factor model for collaborative filtering
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
Benjamin M. Marlin, Richard S. Zemel
ICASSP
2011
IEEE
12 years 8 months ago
Multiple speaker tracking using a microphone array by combining auditory processing and a gaussian mixture cardinalized probabil
Tracking speakers is an important application in smart environments. Acoustic tracking using microphone arrays is a challenging task due to two major reasons: On the one hand, mul...
Axel Plinge, Daniel Hauschildt, Marius H. Hennecke...
ICCV
2007
IEEE
13 years 6 months ago
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Bohyung Han, Seong-Wook Joo, Larry S. Davis
ICASSP
2011
IEEE
12 years 8 months ago
Rao-Blackwellized particle filter for Gaussian mixture models and application to visual tracking
One of the most important problems in visual tracking is how to incrementally update the appearance model because the appearance of a target object can be easily changed with time...
Jungho Kim, In-So Kweon
IIR
2010
13 years 6 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco