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2007
159views Robotics» more  RSS 2007»
14 years 11 months ago
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
Christian Plagemann, Kristian Kersting, Patrick Pf...
87
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CVPR
2004
IEEE
15 years 11 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Vladimir Pavlovic
JMLR
2010
169views more  JMLR 2010»
14 years 4 months ago
Matrix-Variate Dirichlet Process Mixture Models
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
Zhihua Zhang, Guang Dai, Michael I. Jordan
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
15 years 1 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
93
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INTERSPEECH
2010
14 years 4 months ago
Bayesian speaker recognition using Gaussian mixture model and laplace approximation
This paper presents a Bayesian approach for Gaussian mixture model (GMM)-based speaker identification. Some approaches evaluate the speaker score of a test speech utterance using ...
Shih-Sian Cheng, I-Fan Chen, Hsin-Min Wang