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» Learning Models for Object Recognition
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PR
2010
129views more  PR 2010»
15 years 1 months ago
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 3 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
127
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ILP
2005
Springer
15 years 8 months ago
Spatial Clustering of Structured Objects
Clustering is a fundamental task in Spatial Data Mining where data consists of observations for a site (e.g. areal units) descriptive of one or more (spatial) primary units, possib...
Donato Malerba, Annalisa Appice, Antonio Varlaro, ...
IIHMSP
2006
IEEE
137views Multimedia» more  IIHMSP 2006»
15 years 9 months ago
Understanding Human Behavior Using a Language Modeling Approach
Visual analysis of human behavior has generated considerable interest in the field of computer vision because of the wide spectrum of potential applications. In this paper, we pre...
Yu-Ming Liang, Sheng-Wen Shih, Arthur Chun-Chieh S...
CVPR
2005
IEEE
16 years 5 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang