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ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
14 years 2 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
NN
2010
Springer
225views Neural Networks» more  NN 2010»
13 years 6 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani
ICML
2006
IEEE
14 years 8 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
IJCAI
1997
13 years 9 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida
IROS
2009
IEEE
145views Robotics» more  IROS 2009»
14 years 2 months ago
Utilizing prior information to enhance self-supervised aerial image analysis for extracting parking lot structures
Abstract— Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA U...
Young-Woo Seo, Chris Urmson