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» Clustering with Local and Global Regularization
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ICCV
2003
IEEE
14 years 7 months ago
Dominant Sets and Hierarchical Clustering
Dominant sets are a new graph-theoretic concept that has proven to be relevant in partitional (flat) clustering as well as image segmentation problems. However, in many computer v...
Massimiliano Pavan, Marcello Pelillo
SDM
2003
SIAM
110views Data Mining» more  SDM 2003»
13 years 7 months ago
Mixture Models and Frequent Sets: Combining Global and Local Methods for 0-1 Data
We study the interaction between global and local techniques in data mining. Specifically, we study the collections of frequent sets in clusters produced by a probabilistic clust...
Jaakko Hollmén, Jouni K. Seppänen, Hei...
CVPR
2012
IEEE
11 years 8 months ago
2.5D building modeling by discovering global regularities
We introduce global regularities in the 2.5D building modeling problem, to reflect the orientation and placement similarities between planar elements in building structures. Give...
Qian-Yi Zhou, Ulrich Neumann
RECOMB
2007
Springer
14 years 6 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
ICCV
2007
IEEE
14 years 7 months ago
Locally Smooth Metric Learning with Application to Image Retrieval
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Dit-Yan Yeung, Hong Chang