Similarity Learning - IDL - EE

What is Similarity Learning?
Similarity Learning consists of classification and regression on pairwise similarities. In contrast to traditional machine learning, similarity learning does not assume that objects are well represented in a Euclidean feature space. This paradigm is useful for problems in computer vision, bioinformatics, information retrieval and many other areas with diverse an unwieldy object representations.

What is our objective?
This site aims to serve as a repository for similarity data and a forum for evaluating similarity learning algorithms.

Recent News		Recent Additions
Welcome posted on Friday, December 12, 2008 by Maya Gupta Welcome to Similarity Learning. Read All News News Page: 1		New Dataset: "Yeast-SW-5-12" added on Sunday, May 17, 2009 New Dataset: "Yeast-SW-5-7" added on Sunday, May 17, 2009 New Paper: "Similarity-based Classification: Concept..." added on Monday, April 06, 2009 New Paper: "Framework for kernel regularization with..." added on Tuesday, March 10, 2009 New Dataset: "Yeast-Pfam-7-12" added on Tuesday, March 10, 2009 View All Datasets, Papers, Software New Items Page: 1 2 3 4 5 ...