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Mathematical programming : an introduction to optimization
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ISBN: 0824774787 9781351433129 1351433121 9780824774783 Year: 1986 Volume: 102 Publisher: New York, NY : Marcel Dekker,

Concurrency : state models & Java programs.
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ISBN: 9780470093559 0470093552 9780470093560 0470093560 Year: 2006 Publisher: Chichester Wiley

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Concurrency provides a thoroughly updated approach to the basic concepts and techniques behind concurrent programming. Concurrent programming is complex and demands a much more formal approach than sequential programming. In order to develop a thorough understanding of the topic Magee and Kramer present concepts, techniques and problems through a variety of forms: informal descriptions, illustrative examples, abstract models and concrete Java examples. These combine to provide problem patterns and associated solution techniques which enable students to recognise problems and arrive at solutions. New features include: *New Chapter and coverage of Verification. *More student exercises. *Totally updated version of the LTSA tool packaged with the book which makes it easier to use and extends its capabilities.


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Bringing machine learning to software-defined networks
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ISBN: 9789811948749 9789811948732 9789811948756 Year: 2022 Publisher: Singapore : Springer,

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Emerging machine learning techniques bring new opportunities to flexible network control and management. This book focuses on using state-of-the-art machine learning-based approaches to improve the performance of Software-Defined Networking (SDN). It will apply several innovative machine learning methods (e.g., Deep Reinforcement Learning, Multi-Agent Reinforcement Learning, and Graph Neural Network) to traffic engineering and controller load balancing in software-defined wide area networks, as well as flow scheduling, coflow scheduling, and flow migration for network function virtualization in software-defined data center networks. It helps readers reflect on several practical problems of deploying SDN and learn how to solve the problems by taking advantage of existing machine learning techniques. The book elaborates on the formulation of each problem, explains design details for each scheme, and provides solutions by running mathematical optimization processes, conducting simulated experiments, and analyzing the experimental results.


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Introduction to quantum computing : from a layperson to a programmer in 30 steps
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ISBN: 9783030983390 9783030983383 9783030983406 9783030983413 Year: 2022 Publisher: Cham, Switzerland : Springer,

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This textbook introduces quantum computing to readers who do not have much background in linear algebra. The author targets undergraduate and master students, as well as non-CS and non-EE students who are willing to spend about 60 -90 hours seriously learning quantum computing. Readers will be able to write their program to simulate quantum computing algorithms and run on real quantum computers on IBM-Q. Moreover, unlike the books that only give superficial, "hand-waving" explanations, this book uses exact formalism so readers can continue to pursue more advanced topics based on what they learn from this book. Encourages students to embrace uncertainty over the daily classical experience, when encountering quantum phenomena; Uses narrative to start each section with analogies that help students to grasp the critical concept quickly; Uses numerical substitutions, accompanied by Python programming and IBM-Q quantum computer programming, as examples in teaching all critical concepts.


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Nanophotonics and Machine Learning : Concepts, Fundamentals, and Applications
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ISBN: 9783031204739 9783031204722 9783031204746 9783031204753 Year: 2023 Publisher: Cham, Switzerland : Springer,

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This book, the first of its kind, bridges the gap between the increasingly interlinked fields of nanophotonics and artificial intelligence (AI). While artificial intelligence techniques, machine learning in particular, have revolutionized many different areas of scientific research, nanophotonics holds a special position as it simultaneously benefits from AI-assisted device design whilst providing novel computing platforms for AI. This book is aimed at both researchers in nanophotonics who want to utilize AI techniques and researchers in the computing community in search of new photonics-based hardware. The book guides the reader through the general concepts and specific topics of relevance from both nanophotonics and AI, including optical antennas, metamaterials, metasurfaces, and other photonic devices on the one hand, and different machine learning paradigms and deep learning algorithms on the other. It goes on to comprehensively survey inverse techniques for device design, AI-enabled applications in nanophotonics, and nanophotonic platforms for AI. This book will be essential reading for graduate students, academic researchers, and industry professionals from either side of this fast-developing, interdisciplinary field.

The practice of programming
Authors: ---
ISBN: 020161586X 9780201615869 Year: 1999 Publisher: Reading, Mass. Addison-Wesley


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Social media analysis for event detection
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ISBN: 9783031082429 9783031082412 9783031082436 9783031082443 Year: 2022 Publisher: Cham, Switzerland : Springer,

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This book includes chapters which discuss effective and efficient approaches in dealing with various aspects of social media analysis by using machine learning techniques from clustering to deep learning. A variety of theoretical aspects, application domains and case studies are covered to highlight how it is affordable to maximize the benefit of various applications from postings on social media platforms. Social media platforms have significantly influenced and reshaped various social aspects. They have set new means of communication and interaction between people, turning the whole world into a small village where people with internet connect can easily communicate without feeling any barriers. This has attracted the attention of researchers who have developed techniques and tools capable of studying various aspects of posts on social media platforms with main concentration on Twitter. This book addresses challenging applications in this dynamic domain where it is not possible to continue applying conventional techniques in studying social media postings. The content of this book helps the reader in developing own perspective about how to benefit from machine learning techniques in dealing with social media postings and how social media postings may directly influence various applications.


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Wineinformatics : a new data science application
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ISBN: 9789811973697 9789811973680 9789811973703 Year: 2023 Publisher: Singapore : Springer,

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Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data. This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine's specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors. This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book.

Learning Python
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ISBN: 1565924649 9781565924642 Year: 1999 Publisher: Beijing ; Sebastopol, CA : O'Reilly,

Java Swing
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ISBN: 156592455X Year: 1998 Publisher: Sebastopol, CA : O'Reilly & Associates, Inc.,

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