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ATAL
2005
Springer
14 years 3 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
BMCBI
2010
144views more  BMCBI 2010»
13 years 10 months ago
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Background: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuc...
Petr Novák, Pavel Neumann, Jirí Maca...
ICML
1999
IEEE
14 years 10 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
BMCBI
2010
129views more  BMCBI 2010»
13 years 10 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...
SSDBM
2000
IEEE
149views Database» more  SSDBM 2000»
14 years 2 months ago
Coordinating Simultaneous Caching of File Bundles from Tertiary Storage
In a previous paper [Shoshani et al 99], we described a system called STACS (Storage Access Coordination System) for High Energy and Physics (HEP) experiments. These experiments g...
Arie Shoshani, Alex Sim, Luis M. Bernardo, Henrik ...