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JMLR
2010
118views more  JMLR 2010»
13 years 4 months ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell
KDD
2006
ACM
175views Data Mining» more  KDD 2006»
14 years 10 months ago
A mixture model for contextual text mining
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Qiaozhu Mei, ChengXiang Zhai
ICASSP
2009
IEEE
14 years 4 months ago
Comparing maximum a posteriori vector quantization and Gaussian mixture models in speaker verification
Gaussian mixture model - universal background model (GMMUBM) is a standard reference classifier in speaker verification. We have recently proposed a simplified model using vect...
Tomi Kinnunen, Juhani Saastamoinen, Ville Hautam&a...
KDD
2002
ACM
293views Data Mining» more  KDD 2002»
14 years 10 months ago
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
Alexander Ypma, Tom Heskes
ATAL
2007
Springer
14 years 1 months ago
Confidence-based policy learning from demonstration using Gaussian mixture models
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
Sonia Chernova, Manuela M. Veloso