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IJCV
2007
115views more  IJCV 2007»
13 years 7 months ago
Discovering Shape Classes using Tree Edit-Distance and Pairwise Clustering
This paper describes work aimed at the unsupervised learning of shape-classes from shock trees. We commence by considering how to compute the edit distance between weighted trees. ...
Andrea Torsello, Antonio Robles-Kelly, Edwin R. Ha...
ICCV
2009
IEEE
6637views Computer Vision» more  ICCV 2009»
15 years 23 days ago
A Markov Clustering Topic Model for Mining Behaviour in Video
This paper addresses the problem of fully automated mining of public space video data. A novel Markov Clustering Topic Model (MCTM) is introduced which builds on existing Dynami...
Timothy Hospedales, Shaogang Gong, Tao Xiang
ICML
2007
IEEE
14 years 8 months ago
Maximum margin clustering made practical
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
Kai Zhang, Ivor W. Tsang, James T. Kwok
ICML
2007
IEEE
14 years 8 months ago
Cluster analysis of heterogeneous rank data
Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Emp...
Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann
CVPR
2010
IEEE
14 years 4 months ago
Discriminative Clustering for Image Co-segmentation
Purely bottom-up, unsupervised segmentation of a single image into two segments remains a challenging task for computer vision. The co-segmentation problem is the process of joi...
Armand Joulin, Francis Bach, Jean Ponce