— 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...
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...
–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...
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...
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. ...