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» Algorithm Selection using Reinforcement Learning
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ATAL
2009
Springer
15 years 11 months ago
Integrating organizational control into multi-agent learning
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
PR
2007
148views more  PR 2007»
15 years 4 months ago
Learning the best subset of local features for face recognition
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
Berk Gökberk, M. Okan Irfanoglu, Lale Akarun,...
IDEAS
2005
IEEE
149views Database» more  IDEAS 2005»
15 years 10 months ago
An Adaptive Multi-Objective Scheduling Selection Framework for Continuous Query Processing
Adaptive operator scheduling algorithms for continuous query processing are usually designed to serve a single performance objective, such as minimizing memory usage or maximizing...
Timothy M. Sutherland, Yali Zhu, Luping Ding, Elke...
ACL
2010
15 years 2 months ago
Learning Arguments and Supertypes of Semantic Relations Using Recursive Patterns
A challenging problem in open information extraction and text mining is the learning of the selectional restrictions of semantic relations. We propose a minimally supervised boots...
Zornitsa Kozareva, Eduard H. Hovy
AI
1999
Springer
15 years 4 months ago
Introspective Multistrategy Learning: On the Construction of Learning Strategies
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...
Michael T. Cox, Ashwin Ram