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Showing 1 - 12 of 12 results for “runze li”
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  • Design and Modeling for Computer Experiments

    by Kai-Tai Fang, Runze Li, Agus Sudjianto ...
    Series series Chapman & Hall/CRC Computer Science & Data Analysis
    Computer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences. Successful use of a simulation model, however, requires careful interrogation of the model through systematic computer experiments. While specific theoretical/mathematical examinations of computer experim ... Read more

    $70.99 USD

  • Statistical Foundations of Data Science

    by Jianqing Fan, Runze Li, Cun-Hui Zhang, Hui Zou ...
    Series series Chapman & Hall/CRC Data Science Series
    Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and ... Read more

    $171.99 USD

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  • Understanding Deep Learning

    by Simon J.D. Prince ...
    An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent ... Read more

    $54.99 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

  • 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

  • Generalized Additive Models

    An Introduction with R, Second Edition

    by Simon N. Wood ...
    Series series Chapman & Hall/CRC Texts in Statistical Science
    The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before ... Read more

    $125.99 USD

  • Regularized System Identification

    Learning Dynamic Models from Data

    by Gianluigi Pillonetto, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, Lennart Ljung ...
    Series series Engineering (R0)
    This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The ... Read more

    Free

  • 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

  • Handbook of Monte Carlo Methods

    by Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev ...
    Series Book 706 - Wiley Series in Probability and Statistics
    A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applicationsMore and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the ... Read more

    $154.00 USD

  • Probabilistic Machine Learning

    Advanced Topics

    by Kevin P. Murphy ...
    Series series Adaptive Computation and Machine Learning series
    An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics ... Read more

    $92.99 USD

  • Probability, Random Variables, and Random Processes

    Theory and Signal Processing Applications

    by John J. Shynk ...
    Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that ... Read more

    $142.00 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

    Free