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SAC
2005
ACM
15 years 3 months 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
ATAL
2005
Springer
15 years 3 months ago
Automatic computer game balancing: a reinforcement learning approach
Designing agents whose behavior challenges human players adequately is a key issue in computer games development. This work presents a novel technique, based on reinforcement lear...
Gustavo Andrade, Geber Ramalho, Hugo Santana, Vinc...
CIKM
2005
Springer
15 years 3 months ago
Privacy leakage in multi-relational databases via pattern based semi-supervised learning
In multi-relational databases, a view, which is a context- and content-dependent subset of one or more tables (or other views), is often used to preserve privacy by hiding sensiti...
Hui Xiong, Michael Steinbach, Vipin Kumar
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 3 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
ITICSE
2004
ACM
15 years 3 months ago
Generation as method for explorative learning in computer science education
The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advant...
Andreas Kerren