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STOC
2005
ACM
129views Algorithms» more  STOC 2005»
16 years 7 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
CVPR
2007
IEEE
16 years 9 months ago
Learning Local Image Descriptors
In this paper we study interest point descriptors for image matching and 3D reconstruction. We examine the building blocks of descriptor algorithms and evaluate numerous combinati...
Simon A. J. Winder, Matthew Brown
ICDM
2005
IEEE
117views Data Mining» more  ICDM 2005»
16 years 16 days ago
On Learning Asymmetric Dissimilarity Measures
Many practical applications require that distance measures to be asymmetric and context-sensitive. We introduce Context-sensitive Learnable Asymmetric Dissimilarity (CLAD) measure...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
ISVC
2010
Springer
15 years 5 months ago
Learning Scene Entries and Exits Using Coherent Motion Regions
We present a novel framework to reliably learn scene entry and exit locations using coherent motion regions formed by weak tracking data. We construct “entities” from weak trac...
Matthew Nedrich, James W. Davis
JMLR
2006
140views more  JMLR 2006»
15 years 6 months ago
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Masashi Sugiyama