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» Adapting RBF Neural Networks to Multi-Instance Learning
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ESANN
2000
13 years 9 months ago
Local input-output stability of recurrent networks with time-varying weights
Abstract. We present local conditions for input-output stability of recurrent neural networks with time-varying parameters introduced for instance by noise or on-line adaptation. T...
Jochen J. Steil
NN
1998
Springer
13 years 7 months ago
A tennis serve and upswing learning robot based on bi-directional theory
We experimented on task-level robot learning based on bi-directional theory. The via-point representation was used for ‘learning by watching’. In our previous work, we had a r...
Hiroyuki Miyamoto, Mitsuo Kawato
ICANN
2003
Springer
14 years 25 days ago
A Comparison of Model Aggregation Methods for Regression
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
Zafer Barutçuoglu
AIIDE
2009
13 years 8 months ago
Optimization of Platform Game Levels for Player Experience
We demonstrate an approach to modelling the effects of certain parameters of platform game levels on the players' experience of the game. A version of Super Mario Bros has be...
Chris Pedersen, Julian Togelius, Georgios N. Yanna...
ESANN
2000
13 years 9 months ago
Learning VOR-like stabilization reflexes in robots
We present a binocular robot that learns compensatory camera movements for image stabilization purposes. Most essential in achieving satisfactory image stabilization performance i...
Francesco Panerai, Giorgio Metta, Giulio Sandini