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» A theory of learning with similarity functions
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ICCV
2007
IEEE
16 years 1 months ago
Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification
We address the problem of visual category recognition by learning an image-to-image distance function that attempts to satisfy the following property: the distance between images ...
Andrea Frome, Yoram Singer, Fei Sha, Jitendra Mali...
ECIR
2010
Springer
15 years 1 months ago
Learning to Select a Ranking Function
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Jie Peng, Craig Macdonald, Iadh Ounis
CVPR
2010
IEEE
15 years 8 months ago
An Approach to Vectorial Total Variation based on Geometric Measure Theory
We analyze a previously unexplored generalization of the scalar total variation to vector-valued functions, which is motivated by geometric measure theory. A complete mathematical...
Bastian Goldluecke, Daniel Cremers
100
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BMCBI
2008
141views more  BMCBI 2008»
14 years 12 months ago
Functional discrimination of membrane proteins using machine learning techniques
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
M. Michael Gromiha, Yukimitsu Yabuki
CEC
2007
IEEE
15 years 6 months ago
A simple genetic algorithm for music generation by means of algorithmic information theory
— Recent large scale experiments have shown that the Normalized Information Distance, an algorithmic information measure, is among the best similarity metrics for melody classiï¬...
Manuel Alfonseca, Manuel Cebrián, Alfonso O...