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SAC
2005
ACM
16 years 3 days ago
Privacy preserving learning in negotiation
Machine learning techniques are widely used in negotiation systems. To get more accurate and satisfactory learning results, negotiation parties have the desire to employ learning ...
Sheng Zhang, Fillia Makedon
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
16 years 2 days ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 2 days 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
ECP
1997
Springer
105views Robotics» more  ECP 1997»
15 years 10 months ago
Planning, Learning, and Executing in Autonomous Systems
Systems that act autonomously in the environment have to be able to integrate three basic behaviors: planning, execution, and learning. Planning involves describing a set of action...
Ramón García-Martínez, Daniel...
ECML
1998
Springer
15 years 10 months ago
Predicate Invention and Learning from Positive Examples Only
Previous bias shift approaches to predicate invention are not applicable to learning from positive examples only, if a complete hypothesis can be found in the given language, as ne...
Henrik Boström