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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
14 years 7 days ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
SPRINGSIM
2008
13 years 9 months ago
Predicting hepatic disposition properties of cationic drugs using a physiologically based, agent-oriented In Silico Liver
The In Silico Liver (ISL) plugs together autonomous software objects that represent hepatic components at different scales and levels of details. ISL parameters sensitive to drug-...
Li Yan, Sunwoo Park, Shahab Sheikh-Bahaei, Glen E....
CIBCB
2009
IEEE
13 years 8 months ago
Application of machine learning approaches on quantitative structure activity relationships
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
Mariusz Butkiewicz, Ralf Mueller, Danilo Selic, Er...
ACTAC
2006
126views more  ACTAC 2006»
13 years 7 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
CLEIEJ
2007
152views more  CLEIEJ 2007»
13 years 7 months ago
Gene Expression Analysis using Markov Chains extracted from RNNs
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...