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IJCAI
1997
15 years 8 months ago
An Effective Learning Method for Max-Min Neural Networks
Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ m...
Loo-Nin Teow, Kia-Fock Loe
NPL
1998
129views more  NPL 1998»
15 years 6 months ago
Extraction of Logical Rules from Neural Networks
A new architecture and method for feature selection and extraction of logical rules from neural networks trained with backpropagation algorithm is presented. The network consists ...
Wlodzislaw Duch, Rafal Adamczak, Krzysztof Grabcze...
IDEAL
2010
Springer
15 years 5 months ago
Dimension Reduction for Regression with Bottleneck Neural Networks
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
Elina Parviainen
ESANN
2000
15 years 8 months ago
An algorithm for the addition of time-delayed connections to recurrent neural networks
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
Romuald Boné, Michel Crucianu, Jean Pierre ...
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
16 years 1 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson