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» Hierarchical Gaussian Mixture Model
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ICASSP
2011
IEEE
12 years 11 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
NIPS
2007
13 years 9 months ago
Robust Regression with Twinned Gaussian Processes
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...
Andrew Naish-Guzman, Sean B. Holden
JMLR
2010
141views more  JMLR 2010»
13 years 2 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
WACV
2008
IEEE
14 years 2 months ago
Background Subtraction for Temporally Irregular Dynamic Textures
In the traditional mixture of Gaussians background model, the generating process of each pixel is modeled as a mixture of Gaussians over color. Unfortunately, this model performs ...
Gerald Dalley, Joshua Migdal, W. Eric L. Grimson
ICASSP
2010
IEEE
13 years 7 months ago
Under-determined convolutive blind source separation using spatial covariance models
This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency d...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...