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NIPS
1994
13 years 9 months ago
Learning to Play the Game of Chess
This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial...
Sebastian Thrun
OL
2011
217views Neural Networks» more  OL 2011»
13 years 1 months ago
Privacy-preserving linear programming
Abstract. We propose a privacy-preserving formulation of a linear program whose constraint matrix is partitioned into groups of columns where each group of columns and its correspo...
O. L. Mangasarian
IJCNN
2008
IEEE
14 years 2 months ago
A quantum calculus formulation of dynamic programming and ordered derivatives
— Much recent research activity has focused on the theory and application of quantum calculus. This branch of mathematics continues to find new and useful applications and there ...
John Seiffertt, Donald C. Wunsch
IJCNN
2006
IEEE
14 years 1 months ago
Cellular SRN Trained by Extended Kalman Filter Shows Promise for ADP
— Cellular simultaneous recurrent neural network has been suggested to be a function approximator more powerful than the MLP’s, in particular for solving approximate dynamic pr...
Roman Ilin, Robert Kozma, Paul J. Werbos
ESANN
2006
13 years 9 months ago
Optimal design of hierarchical wavelet networks for time-series forecasting
The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each sub-wavelet neural network automatically. Base...
Yuehui Chen, Bo Yang, Ajith Abraham