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» Unsupervised Greedy Learning of Finite Mixture Models
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ACL
2012
11 years 10 months ago
A Nonparametric Bayesian Approach to Acoustic Model Discovery
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Chia-ying Lee, James R. Glass
ICVGIP
2004
13 years 9 months ago
A Framework for Activity Recognition and Detection of Unusual Activities
In this paper we present a simple framework for activity recognition based on a model of multi-layered finite state machines, built on top of a low level image processing module f...
Dhruv Mahajan, Nipun Kwatra, Sumit Jain, Prem Kalr...
CVPR
2012
IEEE
11 years 10 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
DATAMINE
2006
166views more  DATAMINE 2006»
13 years 7 months ago
Accelerated EM-based clustering of large data sets
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...
Jakob J. Verbeek, Jan Nunnink, Nikos A. Vlassis
ICCV
2003
IEEE
14 years 9 months ago
Bayesian Clustering of Optical Flow Fields
We present a method for unsupervised learning of classes of motions in video. We project optical flow fields to a complete, orthogonal, a-priori set of basis functions in a probab...
Jesse Hoey, James J. Little