199 search results - page 14 / 40 » Accuracy of distance metric learning algorithms |
204
Voted
COMPGEOM
2011
ACM
14 years 4 months ago
2011
ACM
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...
ECML
2005
Springer
15 years 6 months ago
2005
Springer
Abstract. Rule induction has attracted a great deal of attention in Machine Learning and Data Mining. However, generating rules is not an end in itself because their applicability ...
84
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IJBIDM
2007
15 years 11 days ago
2007
: The k-nearest neighbour (KNN) technique is a simple yet effective method for classification. In this paper, we propose an efficient weighted nearest neighbour classification algo...
115
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ICML
2004
IEEE
16 years 1 months ago
2004
IEEE
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
169
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CVPR
2012
IEEE
13 years 2 months ago
2012
IEEE
Metric learning is a fundamental problem in computer vision. Different features and algorithms may tackle a problem from different angles, and thus often provide complementary inf...