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» The complexity of stochastic sequences
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INFORMATICALT
2010
103views more  INFORMATICALT 2010»
14 years 6 months ago
Multistage K-Means Clustering for Scenario Tree Construction
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...
GLOBECOM
2007
IEEE
15 years 1 months ago
Optimal Downlink OFDMA Subcarrier, Rate, and Power Allocation with Linear Complexity to Maximize Ergodic Weighted-Sum Rates
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...
Ian C. Wong, Brian L. Evans
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 6 months ago
Model-Based Reinforcement Learning in a Complex Domain
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...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
IEEEICCI
2003
IEEE
15 years 5 months ago
Signal Classification through Multifractal Analysis and Complex Domain Neural Networks
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....
COLT
2001
Springer
15 years 4 months ago
Intrinsic Complexity of Learning Geometrical Concepts from Positive Data
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...
Sanjay Jain, Efim B. Kinber