Zdravko Markov's Books

Data Science and Machine Learning

Mathematical and Statistical Methods

By: Dirk P. Kroese,Zdravko Botev,Thomas Taimre,Radislav Vaisman

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Data Science and Machine Learning

Mathematical and Statistical Methods

By: Dirk P. Kroese,Zdravko Botev,Thomas Taimre,Radislav Vaisman

Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

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Page Count

538

Publisher

CRC Press

Published Date

ISBN 10

1000730778

ISBN 13

9781000730777

Handbook of Monte Carlo Methods

By: Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev

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Handbook of Monte Carlo Methods

By: Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev

A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More 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 Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.

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Page Count

627

Publisher

John Wiley & Sons

Published Date

ISBN 10

1118014952

ISBN 13

9781118014950

Language Modeling for Automatic Speech Recognition of Inflective Languages

An Applications-Oriented Approach Using Lexical Data

By: Gregor Donaj,Zdravko Kačič

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Language Modeling for Automatic Speech Recognition of Inflective Languages

An Applications-Oriented Approach Using Lexical Data

By: Gregor Donaj,Zdravko Kačič

This book covers language modeling and automatic speech recognition for inflective languages (e.g. Slavic languages), which represent roughly half of the languages spoken in Europe. These languages do not perform as well as English in speech recognition systems and it is therefore harder to develop an application with sufficient quality for the end user. The authors describe the most important language features for the development of a speech recognition system. This is then presented through the analysis of errors in the system and the development of language models and their inclusion in speech recognition systems, which specifically address the errors that are relevant for targeted applications. The error analysis is done with regard to morphological characteristics of the word in the recognized sentences. The book is oriented towards speech recognition with large vocabularies and continuous and even spontaneous speech. Today such applications work with a rather small number of languages compared to the number of spoken languages.

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Springer

Published Date

ISBN 10

3319416073

ISBN 13

9783319416076

Student Solutions Manual to accompany Simulation and the Monte Carlo Method, Student Solutions Manual

By: Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev,Reuven Y. Rubinstein

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Student Solutions Manual to accompany Simulation and the Monte Carlo Method, Student Solutions Manual

By: Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev,Reuven Y. Rubinstein

This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB® programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.

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Page Count

204

Publisher

John Wiley & Sons

Published Date

ISBN 10

0470285303

ISBN 13

9780470285305

An Advanced Course in Probability and Stochastic Processes

By: Dirk P. Kroese,Zdravko Botev

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An Advanced Course in Probability and Stochastic Processes

By: Dirk P. Kroese,Zdravko Botev

An Advanced Course in Probability and Stochastic Processes provides a modern and rigorous treatment of probability theory and stochastic processes at an upper undergraduate and graduate level. Starting with the foundations of measure theory, this book introduces the key concepts of probability theory in an accessible way, providing full proofs and extensive examples and illustrations. Fundamental stochastic processes such as Gaussian processes, Poisson random measures, Lévy processes, Markov processes, and Itô processes are presented and explored in considerable depth, showcasing their many interconnections. Special attention is paid to martingales and the Wiener process and their central role in the treatment of stochastic integrals and stochastic calculus. This book includes many exercises, designed to test and challenge the reader and expand their skillset. An Advanced Course in Probability and Stochastic Processes is meant for students and researchers who have a solid mathematical background and who have had prior exposure to elementary probability and stochastic processes. Key Features: Focus on mathematical understanding Rigorous and self-contained Accessible and comprehensive High-quality illustrations Includes essential simulation algorithms Extensive list of exercises and worked-out examples Elegant and consistent notation

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Page Count

378

Publisher

CRC Press

Published Date

ISBN 10

1003828655

ISBN 13

9781003828655

Spatio-Temporal Data Streams

By: Zdravko Galić

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Spatio-Temporal Data Streams

By: Zdravko Galić

This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.

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Page Count

116

Publisher

Springer

Published Date

ISBN 10

1493965751

ISBN 13

9781493965755

Data Mining the Web

Uncovering Patterns in Web Content, Structure, and Usage

By: Zdravko Markov,Daniel T. Larose

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Data Mining the Web

Uncovering Patterns in Web Content, Structure, and Usage

By: Zdravko Markov,Daniel T. Larose

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).

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Page Count

236

Publisher

John Wiley & Sons

Published Date

ISBN 10

0471666556

ISBN 13

9780471666554

Student Solutions Manual to accompany Simulation and the Monte Carlo Method

By: Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev,Reuven Y. Rubinstein

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Student Solutions Manual to accompany Simulation and the Monte Carlo Method

By: Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev,Reuven Y. Rubinstein

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Page Count

188

Publisher

Wiley-Interscience

Published Date

ISBN 10

0470258799

ISBN 13

9780470258798

Book's by Zdravko Markov

Data Science and Machine Learning

Data Science and Machine Learning

Handbook of Monte Carlo Methods

Handbook of Monte Carlo Methods

Language Modeling for Automatic Speech Recognition of Inflective Languages

Language Modeling for Automatic Speech Recognition of Inflective Languages

Student Solutions Manual to accompany Simulation and the Monte Carlo Method, Student Solutions Manual

Student Solutions Manual to accompany Simulation and the Monte Carlo Method, Student Solutions Manual

An Advanced Course in Probability and Stochastic Processes

An Advanced Course in Probability and Stochastic Processes

Spatio-Temporal Data Streams

Spatio-Temporal Data Streams

Data Mining the Web

Data Mining the Web

Student Solutions Manual to accompany Simulation and the Monte Carlo Method

Student Solutions Manual to accompany Simulation and the Monte Carlo Method

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