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» On a theory of learning with similarity functions
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ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
TREC
2004
13 years 10 months ago
Can We Get A Better Retrieval Function From Machine?
The quality of an information retrieval system heavily depends on its retrieval function, which returns a similarity measurement between the query and each document in the collect...
Weiguo Fan, Wensi Xi, Edward A. Fox, Li Wang
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 9 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
KDD
1995
ACM
135views Data Mining» more  KDD 1995»
14 years 9 days ago
Rough Sets Similarity-Based Learning from Databases
Manydata mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues ...
Xiaohua Hu, Nick Cercone
AAMAS
2004
Springer
13 years 8 months ago
Functional Validation in Grid Computing
The development of the World Wide Web has changed the way we think about information. Information on the web is distributed, updates are made asynchronously and resources come onli...
Guofei Jiang, George Cybenko