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» Learning Gaussian processes from multiple tasks
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PR
2010
129views more  PR 2010»
15 years 1 months ago
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
CORR
2006
Springer
107views Education» more  CORR 2006»
15 years 3 months ago
Dense Gaussian Sensor Networks: Minimum Achievable Distortion and the Order Optimality of Separation
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements...
Nan Liu, Sennur Ulukus
CAS
2007
87views more  CAS 2007»
15 years 3 months ago
An Accelerated Algorithm for Density Estimation in Large Databases Using Gaussian Mixtures
Today, with the advances of computer storage and technology, there are huge datasets available, offering an opportunity to extract valuable information. Probabilistic approaches ...
Alvaro Soto, Felipe Zavala, Anita Araneda
130
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CVPR
2009
IEEE
16 years 10 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...
MLMI
2004
Springer
15 years 8 months ago
Speaker Indexing in Audio Archives Using Gaussian Mixture Scoring Simulation
Speaker indexing has recently emerged as an important task due to the rapidly growing volume of audio archives. Current filtration techniques still suffer from problems both in acc...
Hagai Aronowitz, David Burshtein, Amihood Amir