Machine Learning: A Bayesian and Optimization Perspective (Net Developers)

3.83 avg rating
( 6 ratings by Goodreads )
 
9780128015223: Machine Learning: A Bayesian and Optimization Perspective (Net Developers)

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques – together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts.

The book builds carefully from the basic classical methods  to  the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for  different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models.

  • All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods.
  • The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling.
  • Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied.
  • MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.

"synopsis" may belong to another edition of this title.

About the Author:

Sergios Theodoridis is Professor of Signal Processing and Machine Learning in the Department of Informatics and Telecommunications of the University of Athens.

He is the co-author of the bestselling book, Pattern Recognition, and the co-author of Introduction to Pattern Recognition: A MATLAB Approach.

He serves as Editor-in-Chief for the IEEE Transactions on Signal Processing, and he is the co-Editor in Chief with Rama Chellapa for the Academic

Press Library in Signal Processing.

He has received a number of awards including the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2009 IEEE Computational Intelligence Society Transactions on Neural Networks Outstanding Paper Award, the 2014 IEEE Signal Processing Society Education Award, the EURASIP 2014 Meritorious Service Award, and he has served as a Distinguished Lecturer for the IEEE Signal Processing Society and the IEEE Circuits and Systems Society. He is a Fellow of EURASIP and a Fellow of IEEE.

Review:

"Overall, this text is well organized and full of details suitable for advanced graduate and postgraduate courses, as well as scholars..." --Computing Reviews

"Machine Learning: A Bayesian and Optimization Perspective", Academic Press, 2105, by Sergios Theodoridis is a wonderful book, up to date and rich in detail. It covers a broad selection of topics ranging from classical regression and classification techniques to more recent ones including sparse modeling, convex optimization, Bayesian learning, graphical models and neural networks, giving it a very modern feel and making it highly relevant in the deep learning era. While other widely used machine learning textbooks tend to sacrifice clarity for elegance, Professor Theodoridis provides you with enough detail and insights to understand the "fine print". This makes the book indispensable for the active machine learner." --Prof. Lars Kai Hansen, DTU Compute - Dept. Applied Mathematics and Computer Science Technical University of Denmark

"Before the publication of Machine Learning: A Bayesian and Optimization Perspective, I had the opportunity to review one of the chapters in the book (on Monte Carlo methods). I have published actively in this area, and so I was curious how S. Theodoridis would write about it. I was utterly impressed. The chapter presented the material with an optimal mix of theoretical and practical contents in very clear manner and with information for a wide range of readers, from newcomers to more advanced readers. This raised my curiosity to read the rest of the book once it was published. I did it and my original impressions were further reinforced. S. Theodoridis has a great capability to disentangle the important from the unimportant and to make the most of the used space for writing. His text is rich with insights about the addressed topics that are not only helpful for novices but also for seasoned researchers. It goes without saying that my department adopted his book as a textbook in the course on machine learning." --Petar M. Djurić, Ph.D. SUNY Distinguished Professor Department of Electrical and Computer Engineering Stony Brook University, Stony Brook, USA.

"As someone who has taught graduate courses in pattern recognition for over 35 years, I have always looked for a rigorous book that is current and appealing to students with widely varying backgrounds. The book on Machine Learning by Sergios Theodoridis has struck the perfect balance in explaining the key (traditional and new) concepts in machine learning in a way that can be appreciated by undergraduate and graduate students as well as practicing engineers and scientists. The chapters have been written in a self-consistent way, which will help instructors to assemble different sections of the book to suit the background of students" --Rama Cellappa, Distinguished University Professor, Minta Martin Professor of Engineering, Chair, Department of Electrical and Computer Engineering, University of Maryland, USA.

"About this title" may belong to another edition of this title.

Top Search Results from the AbeBooks Marketplace

1.

Theodoridis, Sergios
Published by Academic Press (2015)
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Quantity Available: > 20
Seller
Books2Anywhere
(Fairford, GLOS, United Kingdom)
Rating
[?]

Book Description Academic Press, 2015. HRD. Book Condition: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Bookseller Inventory # FD-9780128015223

More Information About This Seller | Ask Bookseller a Question

Buy New
43.08
Convert Currency

Add to Basket

Shipping: 9
From United Kingdom to U.S.A.
Destination, Rates & Speeds

2.

Theodoridis, Sergios
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Quantity Available: 2
Seller
GreatBookPrices
(Columbia, MD, U.S.A.)
Rating
[?]

Book Description Book Condition: New. Bookseller Inventory # 22181971-n

More Information About This Seller | Ask Bookseller a Question

Buy New
52.42
Convert Currency

Add to Basket

Shipping: 2.03
Within U.S.A.
Destination, Rates & Speeds

3.

Sergios Theodoridis
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Quantity Available: 4
Seller
Book Storm
(HOUSTON, TX, U.S.A.)
Rating
[?]

Book Description Book Condition: New. Brand New books on affordable price.Shipping method: Standard & Expedite, Standard takes 7-8 and Expedited takes 4-6 working days. Due to the constantly changing USPS regulations regarding shipments to APO/FPO addresses we are not currently shipping. Bookseller Inventory # 0128015225-P07

More Information About This Seller | Ask Bookseller a Question

Buy New
54.52
Convert Currency

Add to Basket

Shipping: FREE
Within U.S.A.
Destination, Rates & Speeds

4.

Dr. Sergios Theodoridis
Published by Elsevier Science Publishing Co Inc, United States (2015)
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Hardcover Quantity Available: 10
Seller
The Book Depository
(London, United Kingdom)
Rating
[?]

Book Description Elsevier Science Publishing Co Inc, United States, 2015. Hardback. Book Condition: New. Language: English . Brand New Book. This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. Bookseller Inventory # AA59780128015223

More Information About This Seller | Ask Bookseller a Question

Buy New
56.47
Convert Currency

Add to Basket

Shipping: FREE
From United Kingdom to U.S.A.
Destination, Rates & Speeds

5.

Dr. Sergios Theodoridis
Published by Elsevier Science Publishing Co Inc, United States (2015)
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Hardcover Quantity Available: 10
Seller
The Book Depository US
(London, United Kingdom)
Rating
[?]

Book Description Elsevier Science Publishing Co Inc, United States, 2015. Hardback. Book Condition: New. Language: English . Brand New Book. This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. Bookseller Inventory # AA59780128015223

More Information About This Seller | Ask Bookseller a Question

Buy New
58.50
Convert Currency

Add to Basket

Shipping: FREE
From United Kingdom to U.S.A.
Destination, Rates & Speeds

6.

Sergios Theodoridis
Published by Elsevier Science 2015-05-19, London (2015)
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Hardcover Quantity Available: 5
Seller
Blackwell's
(Oxford, OX, United Kingdom)
Rating
[?]

Book Description Elsevier Science 2015-05-19, London, 2015. hardback. Book Condition: New. Bookseller Inventory # 9780128015223

More Information About This Seller | Ask Bookseller a Question

Buy New
55.99
Convert Currency

Add to Basket

Shipping: 3
From United Kingdom to U.S.A.
Destination, Rates & Speeds

7.

Sergios Theodoridis
Published by Academic Press (2015)
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Hardcover First Edition Quantity Available: 1
Seller
Irish Booksellers
(Rumford, ME, U.S.A.)
Rating
[?]

Book Description Academic Press, 2015. Hardcover. Book Condition: New. book. Bookseller Inventory # 0128015225

More Information About This Seller | Ask Bookseller a Question

Buy New
62.01
Convert Currency

Add to Basket

Shipping: FREE
Within U.S.A.
Destination, Rates & Speeds

8.

Sergios Theodoridis
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Quantity Available: 2
Seller
BWB
(Valley Stream, NY, U.S.A.)
Rating
[?]

Book Description Book Condition: New. Depending on your location, this item may ship from the US or UK. Bookseller Inventory # 97801280152230000000

More Information About This Seller | Ask Bookseller a Question

Buy New
64.34
Convert Currency

Add to Basket

Shipping: FREE
Within U.S.A.
Destination, Rates & Speeds

9.

Theodoridis, Sergios
Published by Elsevier Science & Technology
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Quantity Available: 8
Seller
TextbookRush
(Grandview Heights, OH, U.S.A.)
Rating
[?]

Book Description Elsevier Science & Technology. Book Condition: Brand New. Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy. Bookseller Inventory # 40955844

More Information About This Seller | Ask Bookseller a Question

Buy New
61.76
Convert Currency

Add to Basket

Shipping: 3.07
Within U.S.A.
Destination, Rates & Speeds

10.

Theodoridis, Sergios
Published by Academic Pr (2015)
ISBN 10: 0128015225 ISBN 13: 9780128015223
New Quantity Available: 8
Seller
Paperbackshop-US
(Wood Dale, IL, U.S.A.)
Rating
[?]

Book Description Academic Pr, 2015. HRD. Book Condition: New. New Book. Shipped from US within 10 to 14 business days. Established seller since 2000. Bookseller Inventory # TE-9780128015223

More Information About This Seller | Ask Bookseller a Question

Buy New
62.15
Convert Currency

Add to Basket

Shipping: 3.07
Within U.S.A.
Destination, Rates & Speeds

There are more copies of this book

View all search results for this book