Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Inter...
In this overview paper we motivate the need for and research issues arising from a new model of data processing. In this model, data does not take the form of persistent relations...
Brian Babcock, Shivnath Babu, Mayur Datar, Rajeev ...
— Nanoscale technologies provide both challenges and opportunities. We show that the issues and potential solutions facing designers are technology independent and arise mainly f...
This paper proposes selective update and cooperation strategies for parameter estimation in distributed adaptive sensor networks. A setmembership filtering approach is employed t...
Stefan Werner, Yih-Fang Huang, Marcello L. R. de C...
This paper explores the approximation properties of a unique basis expansion, which realizes a bilinear frequency warping between a continuous-time signal and its discrete-time re...