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» Sublinear Optimization for Machine Learning
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GECCO
2008
Springer
121views Optimization» more  GECCO 2008»
13 years 8 months ago
Fast rule representation for continuous attributes in genetics-based machine learning
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
Jaume Bacardit, Natalio Krasnogor
ICML
2005
IEEE
14 years 8 months ago
Learning predictive representations from a history
Predictive State Representations (PSRs) have shown a great deal of promise as an alternative to Markov models. However, learning a PSR from a single stream of data generated from ...
Eric Wiewiora
ICALT
2006
IEEE
14 years 1 months ago
Metadata Challenges for Situational Properties of Learning Objects
raction of free-standing metadata describing learning objects is typified by an analytical model which primarily focuses on the encoding of discrete properties pertaining to the ...
Baden Hughes, Roderick A. Farmer
COLT
1993
Springer
13 years 11 months ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung
ICML
2010
IEEE
13 years 8 months ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet