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ATAL
2007
Springer
13 years 11 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
ICRA
2008
IEEE
146views Robotics» more  ICRA 2008»
14 years 1 months ago
Visual servoing based on Gaussian mixture models
— In this paper we present a novel approach to robust visual servoing. This method removes the feature tracking step from a typical visual servoing algorithm. We do not need corr...
A. H. Abdul Hafez, Supreeth Achar, C. V. Jawahar
IJCNN
2007
IEEE
14 years 1 months ago
Iterative Feature Selection in Gaussian Mixture Clustering with Automatic Model Selection
— This paper proposes an algorithm to deal with the feature selection in Gaussian mixture clustering by an iterative way: the algorithm iterates between the clustering and the un...
Hong Zeng, Yiu-ming Cheung
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 7 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
ICASSP
2009
IEEE
14 years 2 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...