Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
Abstract— In this paper, we propose a novel, effective and efficient probabilistic pruning criterion for probabilistic similarity queries on uncertain data. Our approach support...
Thomas Bernecker, Tobias Emrich, Hans-Peter Kriege...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Bluetooth is a promising new technology that enables portable devices to form short-range wireless ad hoc networks and relies on spread spectrum frequency hopping (FH) techniques f...
This paper presents an approach that integrates computational intelligence/soft computing paradigms with clinical investigation methods and knowledge. Computational intelligence m...
Nicolae Varachiu, Cynthia Karanicolas, Mihaela Uli...