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» Discriminative K-means for Clustering
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ICML
2007
IEEE
16 years 14 days ago
Best of both: a hybridized centroid-medoid clustering heuristic
Although each iteration of the popular kMeans clustering heuristic scales well to larger problem sizes, it often requires an unacceptably-high number of iterations to converge to ...
Nizar Grira, Michael E. Houle
AAAI
2012
13 years 2 months ago
Discriminative Clustering via Generative Feature Mapping
Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is ad...
Liwei Wang, Xiong Li, Zhuowen Tu, Jiaya Jia
ICONIP
2008
15 years 1 months ago
Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity
In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kol...
Tina Geweniger, Frank-Michael Schleif, Alexander H...
CVPR
2012
IEEE
13 years 2 months ago
Discovering discriminative action parts from mid-level video representations
We describe a mid-level approach for action recognition. From an input video, we extract salient spatio-temporal structures by forming clusters of trajectories that serve as candi...
Michalis Raptis, Iasonas Kokkinos, Stefano Soatto
ICPR
2010
IEEE
15 years 3 months ago
Cluster-Pairwise Discriminant Analysis
Pattern recognition problems often suffer from the larger intra-class variation due to situation variations such as pose, walking speed, and clothing variations in gait recognition...
Yasushi Makihara, Yasushi Yagi