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ICML
2004
IEEE
16 years 7 months ago
Utile distinction hidden Markov models
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
Daan Wierstra, Marco Wiering
AI
2009
Springer
16 years 22 days ago
Cost-Based Sampling of Individual Instances
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
William Klement, Peter A. Flach, Nathalie Japkowic...
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
16 years 20 days ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
15 years 11 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
ISLPED
2004
ACM
108views Hardware» more  ISLPED 2004»
15 years 11 months ago
SEPAS: a highly accurate energy-efficient branch predictor
Designers have invested much effort in developing accurate branch predictors with short learning periods. Such techniques rely on exploiting complex and relatively large structure...
Amirali Baniasadi, Andreas Moshovos