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Markov Logic

both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as;

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Markov Logic

both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as;

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Image Processing

in computer vision. The updated version presents new sections on compression via JPEG and MPEG, fractals, fuzzy logic recognition, hidden Markov;

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Statistical Relational Artificial Intelligence

representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus;

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Therapeutic Potential of Furin Inhibition

representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus;

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Statistical Relational Artificial Intelligence

representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus;

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Statistical Relational Artificial Intelligence

representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus;

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Boolean Logic, Expressions and Theories

functions. This procedure utilizes two steps to integrate the hidden Markov model, likelihood ratio test and Boolean functions for discovering;

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Handbook Of Machine Learning - Volume 1

This is a comprehensive book on the theories of artificial intelligence with an emphasis on their applications. It combines fuzzy logic and;

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Markov Chains and Decision Processes for Engineers and Managers

Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and;

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Markov Chains and Decision Processes for Engineers and Managers

Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and;

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Introduction to Hidden Semi-Markov Models

Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction;

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Random Motions in Markov and SemiMarkov Random Environments 2

This book is the second of two volumes on random motions in Markov and semi-Markov random environments. This second volume focuses on high;

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Markov Models for Pattern Recognition

. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions;

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Markov Processes and Applications

This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an;

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Markov Decision Processes

Examines several fundamentals concerning the manner in which Markov decision problems may be properly formulated and the determination;

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Markov Chains

This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end;

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Stochastic Relations

: Foundations for Markov Transition Systems develops the theory of stochastic relations as a basis for Markov transition systems. After an;

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Stochastic Relations

: Foundations for Markov Transition Systems develops the theory of stochastic relations as a basis for Markov transition systems. After an;

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Markov Processes for Stochastic Modeling

This book presents an algebraic development of the theory of countable state space Markov chains with discrete- and continuous-time;

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Statistical Topics and Stochastic Models for Dependent Data with Applications

corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov;

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Semi-Markov Processes

Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time;

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Ergodic Behavior of Markov Processes

The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and;

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Markov Processes

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic;

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Semi-Dirichlet Forms and Markov Processes

This book deals with analytic treatments of Markov processes. Symmetric Dirichlet forms and their associated Markov processes are important;

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Markov Chains

A fascinating and instructive guide to Markov chains for experienced users and newcomers alike This unique guide to Markov chains;

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Inference for Hidden Markov Models and related Models

Inference for Hidden Markov Models and related Models is een boek van Cuvillier Verlag;

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