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TNN
2010
155views Management» more  TNN 2010»
15 years 1 months ago
Incorporating the loss function into discriminative clustering of structured outputs
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
ICCV
2007
IEEE
16 years 8 months ago
Scene Modeling Using Co-Clustering
In this paper, we propose a novel approach for scene modeling. The proposed method is able to automatically discover the intermediate semantic concepts. We utilize Maximization of...
Jingen Liu, Mubarak Shah
ICCV
2011
IEEE
14 years 6 months ago
Source Constrained Clustering
We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
APVIS
2010
15 years 8 months ago
GMap: Visualizing graphs and clusters as maps
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
Emden R. Gansner, Yifan Hu, Stephen G. Kobourov
VISAPP
2008
15 years 8 months ago
Pose Clustering From Stereo Data
Abstract. This article describes an algorithm for pose or motion estimation based on clustering of parameters in the six-dimensional pose space. The parameter samples are computed ...
Ulrich Hillenbrand