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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 10 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
ECAI
2004
Springer
15 years 10 months ago
A Backtracking Strategy for Order-Independent Incremental Learning
Agents that exist in an environment that changes over time, and are able to take into account the temporal nature of experience, are commonly called incremental learners. It is wid...
Nicola Di Mauro, Floriana Esposito, Stefano Ferill...
PKDD
2004
Springer
324views Data Mining» more  PKDD 2004»
15 years 10 months ago
Orange: From Experimental Machine Learning to Interactive Data Mining
Abstract. Orange (www.ailab.si/orange) is a suite for machine learning and data mining. It can be used though scripting in Python or with visual programming in Orange Canvas using ...
Janez Demsar, Blaz Zupan, Gregor Leban, Tomaz Curk
EUROMICRO
2000
IEEE
15 years 9 months ago
Supporting Cooperative Learning of Process Knowledge on the World Wide Web
The WWW makes learning materials widely accessible and provides an environment where people can learn across time and space. However, the simple read-only information structure on...
Weigang Wang, Jörg M. Haake, Jessica Rubart, ...
CIA
2006
Springer
15 years 8 months ago
Market-Inspired Approach to Collaborative Learning
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
Jan Tozicka, Michal Jakob, Michal Pechoucek