Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. ...
Continue readingProbabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. ...
Continue readingThis book constitutes the refereed proceedings of the Second International Conference on Distributed Artificial Intelligence, ...
Continue readingThis book constitutes the thoroughly refereed and peer-reviewed outcome of the Formal Methods and Testing (FORTEST) network ...
Continue readingThe European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery ...
Continue readingMarkov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems ...
Continue readingMarkov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems ...
Continue readingMarkov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be ...
Continue readingModeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends ...
Continue reading“If necessity is the mother of invention, then deregulation is the father, and r- enue management (also known as yield ...
Continue reading(Four areas in one book) This book covers various disciplines in learning and optimization, including perturbation analysis ...
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