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Showing 1 - 12 of 12 results for “ronald ortner”
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  • Decision Making Under Uncertainty and Reinforcement Learning

    Theory and Algorithms

    by Christos Dimitrakakis, Ronald Ortner ...
    Series series Intelligent Technologies and Robotics (R0)
    This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most ... Read more

    $152.09 USD

  • Algorithmic Learning Theory

    27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings

    Edited by Ronald Ortner, Hans Ulrich Simon, Sandra Zilles ...
    Series series Springer Nature Proceedings Computer Science
    This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALT 2016, held in Bari, Italy, in October 2016, co-located with the 19th International Conference on Discovery Science, DS 2016. The 24 regular papers presented in this volume were carefully reviewed and selected from 45 submissions. In addition the book contains 5 abstracts of ... Read more

    $49.99 USD

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  • System Identification

    Theory for the User

    by Lennart Ljung ...
    The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and ... Read more

    $134.99 USD

  • Introduction to Machine Learning, fourth edition

    by Ethem Alpaydin ...
    Series series Adaptive Computation and Machine Learning series
    A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This ... Read more

    $52.99 USD

  • Simulation

    by Sheldon M. Ross ...
    The 5th edition of Ross's Simulation continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions ... Read more

    $71.09 USD

  • Introduction to Bayesian Econometrics

    by Edward Greenberg ...
    This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior ... Read more

    $50.09 USD

  • Probabilistic Machine Learning

    An Introduction

    by Kevin P. Murphy ...
    Series series Adaptive Computation and Machine Learning series
    A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra ... Read more

    $77.99 USD

  • Statistical Analysis Techniques in Particle Physics

    Fits, Density Estimation and Supervised Learning

    by Ilya Narsky, Frank C. Porter ...
    Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students. ... Read more

    $102.00 USD

  • A Course in Statistics with R

    by Prabhanjan N. Tattar, Suresh Ramaiah, B. G. Manjunath ...
    Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in ... Read more

    $94.00 USD

  • Bayesian Essentials with R

    by Christian P. Robert, Jean-Michel Marin ...
    Series series Mathematics and Statistics (R0)
    This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications.Readers are ... Read more

    $98.09 USD

  • Computational Statistics

    by Geof H. Givens, Jennifer A. Hoeting ...
    Series Book 710 - Wiley Series in Computational Statistics
    This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field:OptimizationIntegration and SimulationBootstrappingDensity Estimation and SmoothingWithin these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the ... Read more

    $118.00 USD

  • Statistical Foundations of Actuarial Learning and its Applications

    by Mario V. Wüthrich, Michael Merz ...
    Series series Mathematics and Statistics (R0)
    This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice.Statistical modeling has a wide ... Read more

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