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» On Fitting Mixture Models
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KDD
2003
ACM
191views Data Mining» more  KDD 2003»
16 years 4 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
NIPS
2001
15 years 5 months ago
Latent Dirichlet Allocation
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian m...
David M. Blei, Andrew Y. Ng, Michael I. Jordan
CVPR
2001
IEEE
16 years 6 months ago
Mixtures of Trees for Object Recognition
Efficient detection of objects in images is complicated by variations of object appearance due to intra-class object differences, articulation, lighting, occlusions, and aspect va...
Sergey Ioffe, David A. Forsyth
NIPS
1998
15 years 5 months ago
Robot Docking Using Mixtures of Gaussians
This paper applies the Mixture of Gaussians probabilistic model, combined with Expectation Maximization optimization to the task of summarizing three dimensional range data for a ...
Matthew M. Williamson, Roderick Murray-Smith, Volk...
ICASSP
2011
IEEE
14 years 8 months ago
Integrating binaural cues and blind source separation method for separating reverberant speech mixtures
This paper presents a new method for reverberant speech separation, based on the combination of binaural cues and blind source separation (BSS) for the automatic classification o...
Atiyeh Alinaghi, Wenwu Wang, Philip J. B. Jackson