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The Probabilistic Foundations of Rational Learning

of epistemology. What results from this is a unified account of probabilistic learning in the tradition of Richard Jeffrey's 'radical probabilism'. Along;

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The Probabilistic Foundations of Rational Learning

of epistemology. What results from this is a unified account of probabilistic learning in the tradition of Richard Jeffrey's 'radical probabilism'. Along;

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Foundations of Probabilistic Logic Programming

thus represent an excellent candidate for the integration. Since its birth, the field of Probabilistic Logic Programming has seen a steady;

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Foundations of Probabilistic Programming

covers such elementary questions and more. It provides a state-of-the-art overview of the theoretical underpinnings of modern probabilistic;

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Quantal Response Equilibrium

, learning, and well-specified behavioral modifications of rational choice and rational expectations. The empirical relevance of the theory;

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Foundations of Data Science

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high;

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Inductive Logic Programming

. The papers cover the following topics: propositionalization, logical foundations, implementations, probabilistic ILP, applications in robotics;

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Inductive Logic Programming

. The papers represent well the current breath of ILP research topics such as predicate invention; graph-based learning; spatial learning;

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Probabilistic Methods in Geotechnical Engineering

The proceedings of this conference contain keynote addresses on recent developments in geotechnical reliability and limit state design;

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Foundations of Measurement Volume II: Geometrical, Threshold, and Probabilistic Representationsvolume 2

. Volume II extends the subject in the direction of geometrical, threshold, and probabilistic representations, and Volume III examines;

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Cambridge Studies in Probability, Induction and Decision Theory

of hidden variables. The third part consists of a single extended essay applying probabilistic theories of learning to practical questions;

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Cambridge Studies in Probability, Induction and Decision Theory

of hidden variables. The third part consists of a single extended essay applying probabilistic theories of learning to practical questions;

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Foundations of the Formal Sciences VI: Probabilistic Reasoning and Reasoning with Probabilities

Probabilistic methods are increasingly becoming an important tool in a variety of disciplines including computer science, mathematics;

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Putting Logic In Its Place

) invites the use of probabilistic coherence to constrain rational belief. But this latter project has often involved defining graded beliefs;

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Probabilistic Machine Learning

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian;

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Probabilistic Deep Learning

Probabilistic Deep Learning shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty;

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Risk-Neutral Valuation

This second edition - completely up to date with new exercises - provides a comprehensive and self-contained treatment of the probabilistic;

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Planning with markov Decision Processes

reinforcement learning. Probabilistic planning assumes known models for the agent's goals and domain dynamics, and focuses on determining how the agent;

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Data Mining and Machine Learning

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze;

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Rationality and Dynamic Choice

This is a major contribution to the theory of rational choice which will be of particular interest to philosophers and economists. The;

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Rationality and Dynamic Choice

This is a major contribution to the theory of rational choice which will be of particular interest to philosophers and economists. The;

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Bayesian and grAphical Models for Biomedical Imaging

, e.g. machine learning in medical imaging, have a stronger mathematical focus on the foundations of probabilistic modeling and inference. The;

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The Theory of Info Dynamics Rational Foundations of Information Knowledge Dynam

of information. It establishes the rational foundations of information dynamics and how these foundations relate to the general socio-natural dynamics;

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Semantics of Probabilistic Processes

This book discusses the semantic foundations of concurrent systems with nondeterministic and probabilistic behaviour. Particular attention;

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Laws of Chaos

theoretical framework for the foundations of political economy. It relies on probabilistic and statistical methods of the kind used in the modern;

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Probabilistic Approaches for Geotechnical Site Characterization and Slope Stability Analysis

This is the first book to revisit geotechnical site characterization from a probabilistic point of view and provide rational tools to;

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Computational Learning And Probabilistic Reasoning

learning. The contributions in this volume describe and explore the current developments in computer science and theoretical statistics which;

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