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» Machine learning problems from optimization perspective
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IWANN
1999
Springer
15 years 6 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
ECML
2004
Springer
15 years 6 months ago
Population Diversity in Permutation-Based Genetic Algorithm
Abstract. This paper presents an empirical study of population diversity measure and adaptive control of diversity in the context of a permutation-based algorithm for Traveling Sal...
Kenny Qili Zhu, Ziwei Liu
TEC
2010
120views more  TEC 2010»
14 years 9 months ago
Benefits of a Population: Five Mechanisms That Advantage Population-Based Algorithms
This paper identifies five distinct mechanisms by which a population-based algorithm might have an advantage over a solo-search algorithm in classical optimization. These mechanism...
Adam Prügel-Bennett
MIDDLEWARE
2009
Springer
15 years 9 months ago
Rhizoma: A Runtime for Self-deploying, Self-managing Overlays
Abstract. The trend towards cloud and utility computing infrastructures raises challenges not only for application development, but also for management: diverse resources, changing...
Qin Yin, Adrian Schüpbach, Justin Cappos, And...
ESANN
2006
15 years 3 months ago
Immune Network based Ensembles
This paper presents a new method for constructing ensembles of classifiers based on immune network theory, one of the most interesting paradigms within the field of artificial imm...
Nicolás García-Pedrajas, Colin Fyfe