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» An Efficient Algorithm for Local Distance Metric Learning
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74
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TKDE
2010
168views more  TKDE 2010»
14 years 8 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
ICMCS
2005
IEEE
97views Multimedia» more  ICMCS 2005»
15 years 3 months ago
A computationally efficient 3D shape rejection algorithm
In this paper, we present an efficient 3D shape rejection algorithm for unlabeled 3D markers. The problem is important in domains such as rehabilitation and the performing arts. T...
Yinpeng Chen, Hari Sundaram
75
Voted
TCS
2008
14 years 9 months ago
Distance- k knowledge in self-stabilizing algorithms
Abstract. Many graph problems seem to require knowledge that extends beyond the immediate neighbors of a node. The usual self-stabilizing model only allows for nodes to make decisi...
Wayne Goddard, Stephen T. Hedetniemi, David Pokras...
COMPGEOM
2011
ACM
14 years 1 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
CVPR
2007
IEEE
15 years 11 months ago
Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure
We propose a novel classification approach for automatically detecting pulmonary embolism (PE) from computedtomography-angiography images. Unlike most existing approaches that req...
Jinbo Bi, Jianming Liang