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» On Feature Selection through Clustering
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NIPS
2008
13 years 9 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
IAT
2010
IEEE
13 years 5 months ago
An Interactive Tool for Constrained Clustering with Human Sampling
Abstract--This paper describes an interactive tool for constrained clustering that helps users to select effective constraints efficiently during the constrained clustering process...
Masayuki Okabe, Seiji Yamada
CVPR
2006
IEEE
14 years 9 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
WEBI
2005
Springer
14 years 1 months ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
CIKM
2009
Springer
14 years 2 months ago
Text summarization model based on the budgeted median problem
We propose a multi-document generic summarization model based on the budgeted median problem. Our model selects sentences to generate a summary so that every sentence in the docum...
Hiroya Takamura, Manabu Okumura