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» Learning Distance Functions using Equivalence Relations
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MFCS
2007
Springer
15 years 3 months ago
Evolvability
A framework for analyzing the computational capabilities and the limitations of the evolutionary process of random change guided by selection was recently introduced by Valiant [V...
Leslie G. Valiant
ICML
2010
IEEE
14 years 10 months ago
A DC Programming Approach for Sparse Eigenvalue Problem
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
Mamadou Thiao, Pham Dinh Tao, Le Thi Hoai An
BMCBI
2007
147views more  BMCBI 2007»
14 years 9 months ago
Hon-yaku: a biology-driven Bayesian methodology for identifying translation initiation sites in prokaryotes
Background: Computational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remain...
Yuko Makita, Michiel J. L. de Hoon, Antoine Danchi...
COLT
2007
Springer
15 years 3 months ago
Sketching Information Divergences
When comparing discrete probability distributions, natural measures of similarity are not p distances but rather are informationdivergences such as Kullback-Leibler and Hellinger. ...
Sudipto Guha, Piotr Indyk, Andrew McGregor
AUSAI
2005
Springer
15 years 3 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington