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IJCNN
2008
IEEE
14 years 2 months ago
Numerical condition of feedforward networks with opposite transfer functions
— Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfe...
Mario Ventresca, Hamid R. Tizhoosh
ATAL
2005
Springer
14 years 2 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ICC
2007
IEEE
146views Communications» more  ICC 2007»
14 years 2 months ago
Optimally Mapping an Iterative Channel Decoding Algorithm to a Wireless Sensor Network
–Retransmission based schemes are not suitable for energy constrained wireless sensor networks. Hence, there is an interest in including parity bits in each packet for error cont...
Saad B. Qaisar, Shirish S. Karande, Kiran Misra, H...
INFOCOM
2008
IEEE
14 years 2 months ago
A Distributed Optimization Algorithm for Multi-Hop Cognitive Radio Networks
Cognitive radio (CR) is a revolution in radio technology and is viewed as an enabling technology for dynamic spectrum access. This paper investigates how to design distributed alg...
Yi Shi, Y. Thomas Hou
SODA
2008
ACM
138views Algorithms» more  SODA 2008»
13 years 10 months ago
Fully polynomial time approximation schemes for stochastic dynamic programs
We develop a framework for obtaining Fully Polynomial Time Approximation Schemes (FPTASs) for stochastic univariate dynamic programs with either convex or monotone single-period c...
Nir Halman, Diego Klabjan, Chung-Lun Li, James B. ...