Abstract. In stochastic programming and decision analysis, an important issue consists in the approximate representation of the multidimensional stochastic underlying process in th...
Kristina Sutiene, Dalius Makackas, Henrikas Pranev...
Abstract— In this paper, we propose a resource allocation algorithm for ergodic weighted-sum rate maximization in downlink OFDMA systems. In contrast to most previous research tha...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
This paper describes a system capable of classifying stochastic, self-affine, nonstationary signals produced by nonlinear systems. The classification and analysis of these signals...
Witold Kinsner, V. Cheung, K. Cannons, J. Pear, T....
Intrinsic complexity is used to measure the complexity of learning areas limited by broken-straight lines (called open semi-hulls) and intersections of such areas. Any strategy le...