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1-12 sur 12 résultats pour « faming liang »
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  • Sparse Graphical Modeling for High Dimensional Data

    A Paradigm of Conditional Independence Tests

    par Faming Liang, Bochao Jia ...
    Collections series Chapman & Hall/CRC Monographs on Statistics and Applied Probability
    This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison; unified treatments for missing data and heterogeneous data; efficient methods for joint estimation of multiple ... En savoir plus

    $107.17 CAD

  • Advanced Markov Chain Monte Carlo Methods

    Learning from Past Samples

    par Faming Liang, Chuanhai Liu, Raymond Carroll ...
    Collections Livre 714 - Wiley Series in Computational Statistics
    Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. The application examples are drawn from diverse fields such as bioinformatics, machine learning, social science, combinatorial optimization, and computational ... En savoir plus

    $145.99 CAD

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  • Causal Inference in Statistics

    A Primer

    par Judea Pearl, Madelyn Glymour, Nicholas P. Jewell ...
    CAUSAL INFERENCE IN STATISTICSA PrimerCausality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written ... En savoir plus

    $53.99 CAD

  • Computer Age Statistical Inference

    Algorithms, Evidence, and Data Science

    par Bradley Efron, Trevor Hastie ...
    Collections Livre 5 - Institute of Mathematical Statistics Monographs
    The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating ... En savoir plus

    $81.99 CAD

  • Artificial Intelligence

    With an Introduction to Machine Learning, Second Edition

    par Richard E. Neapolitan, Xia Jiang ...
    Collections series Chapman & Hall/CRC Artificial Intelligence and Robotics Series
    The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.The book is divided into five ... En savoir plus

    $86.99 CAD

  • Introduction to Machine Learning, fourth edition

    par Ethem Alpaydin ...
    Collections 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 ... En savoir plus

    $95.99 CAD

  • Markov Models: An Introduction to Markov Models

    par Steven Taylor ...
    Markov ModelsThis book will offer you an insight into the Hidden Markov Models as well as the Bayesian Networks. Additionally, by reading this book, you will also learn algorithms such as Markov Chain Sampling.Furthermore, this book will also teach you how Markov Models are very relevant when a decision problem is associated with a risk that continues over time, when the timing of occurrenc... ... En savoir plus

    $5.99 CAD ou Gratuit avec Kobo Plus

  • Regularized System Identification

    Learning Dynamic Models from Data

    par Gianluigi Pillonetto, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, Lennart Ljung ...
    Collections 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 ... En savoir plus

    Gratuit

  • Elements of Causal Inference

    Foundations and Learning Algorithms

    par Jonas Peters, Dominik Janzing, Bernhard Scholkopf ...
    Collections series Adaptive Computation and Machine Learning series
    A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data.After explaining the ... En savoir plus

    $51.99 CAD

  • Statistical Analysis Techniques in Particle Physics

    Fits, Density Estimation and Supervised Learning

    par 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. ... En savoir plus

    $140.99 CAD

  • Bayesian Networks

    An Introduction

    par Timo Koski, John Noble ...
    Collections Livre 924 - Wiley Series in Probability and Statistics
    Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions ... En savoir plus

    $120.99 CAD

  • Neural Network Methods in Natural Language Processing

    par Yoav Goldberg, Graeme Hirst ...
    Collections series Synthesis Lectures on Human Language Technologies
    Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data.The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. ... En savoir plus

    $65.99 CAD