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IJCAI
1997
15 years 5 months ago
Law Discovery using Neural Networks
This paper proposes a new connectionist approach to numeric law discovery; i.e., neural networks (law-candidates) are trained by using a newly invented second-order learning algor...
Kazumi Saito, Ryohei Nakano
115
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IJCNN
2006
IEEE
15 years 9 months ago
Divide and Conquer Strategies for MLP Training
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
Smriti Bhagat, Dipti Deodhare
150
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JMLR
2010
227views more  JMLR 2010»
15 years 2 months ago
PyBrain
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a vari...
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, M...
132
Voted
GECCO
2000
Springer
15 years 7 months ago
Modeling GA Performance for Control Parameter Optimization
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
Vincent A. Cicirello, Stephen F. Smith
135
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GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
15 years 7 months ago
Evolutionary Design of Behaviors for Action-Based Environment Modeling by a Mobile Robot
This paper describes an evolutionary way to acquire behaviors of a mobile robot for recognizing environments. We have proposed AEM (Action-based Environment Modeling) approach for...
Seiji Yamada