— For most of wireless services with variable rate transmission, both average rate and rate oscillation are important performance metrics. One often needs to decide how much rate...
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...
The dynamics of the Web and the demand for new, active services are imposing new requirements on Web servers. One such new service is the processing of continuous queries whose ou...
Mohamed A. Sharaf, Alexandros Labrinidis, Panos K....
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
Abstract--We derive a class of algorithms for independent component analysis (ICA) based on maximum likelihood (ML) estimation and perform stability analysis of natural gradient ML...