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