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Notes on Tug-of-War Games and the p-Laplace Equation (SpringerBriefs on PDEs and Data Science)
by Mikko ParviainenThis book addresses the interplay between stochastic processes and partial differential equations. More specifically, it focuses on the connection between the nonlinear p-Laplace equation and the stochastic game called tug-of-war with noise. The connection in this context was discovered approximately 15 years ago and has since provided new insights and approaches. These lecture notes provide a brief but detailed and accessible introduction to the subject and to the more research-oriented literature. The book also presents the parabolic case side by side with the elliptic case, highlighting the fact that elliptic and parabolic equations are close in spirit in certain aspects. Moreover, it covers some parts of the regularity theory for these problems. Graduate students and advanced undergraduate students with a basic understanding of probability and partial differential equations will find this book useful.
Computational Intelligence in Machine Learning: Proceedings of the 2nd International Conference ICCIML 2022 (Lecture Notes in Electrical Engineering #1106)
by Vinit Kumar Gunjan Amit Kumar Jacek M. Zurada Sri Niwas SinghThis volumes comprises select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2022). The contents cover latest research trends and developments in the areas of machine learning, smart cities, IoT, Artificial Intelligence, cyber physical systems, cybernetics, data science, neural network, cognition, among others. It also addresses the comprehensive nature of computational intelligence, AI, ML and DL to emphasize its character in modelling, identification, optimization, prediction, forecasting, and control of future intelligent systems. This volume will be a useful guide to those working as researchers in academia and industry by presenting in-depth fundamental research contributions from a methodological/application perspective in understanding Artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.
Data Science and Artificial Intelligence: First International Conference, DSAI 2023, Bangkok, Thailand, November 27–29, 2023, Proceedings (Communications in Computer and Information Science #1942)
by Chutiporn Anutariya Marcello M. BonsangueThis book constitutes the proceedings of the First International Conference, DSAI 2023, held in Bangkok, Thailand, during November 27–30, 2023. The 22 full papers and the 4 short papers included in this volume were carefully reviewed and selected from 70 submissions. This volume focuses on ideas, methodologies, and cutting-edge research that can drive progress and foster interdisciplinary collaboration in the fields of data science and artificial intelligence.
Maschinelles Lernen: Die Grundlagen
by Alexander JungMaschinelles Lernen (ML) ist zu einem alltäglichen Element in unserem Leben und zu einem Standardwerkzeug für viele Bereiche der Wissenschaft und Technik geworden. Um ML optimal nutzen zu können, ist es wichtig, die zugrunde liegenden Prinzipien zu verstehen. In diesem Buch wird ML als die rechnerische Umsetzung des wissenschaftlichen Prinzips betrachtet. Dieses Prinzip besteht darin, ein Modell eines gegebenen datenerzeugenden Phänomens kontinuierlich anzupassen, indem eine Form des Verlustes, der durch seine Vorhersagen entsteht, minimiert wird.Das Buch schult den Leser darin, verschiedene ML-Anwendungen und -Methoden in drei Komponenten (Daten, Modell und Verlust) aufzuschlüsseln, und hilft ihm so, aus dem riesigen Angebot an vorgefertigten ML-Methoden auszuwählen.Der Drei-Komponenten-Ansatz des Buches erlaubt eine einheitliche und transparente Darstellung verschiedener ML-Techniken. Wichtige Methoden zu Regularisierung, zum Schutz der Privatsphäre und zur Erklärbarkeit von ML-Methoden sind Spezialfälle dieses Drei-Komponenten-Ansatz.
Numerische Analyse von gewöhnlichen und retardierten Differentialgleichungen
by Taketomo Mitsui Guang-Da HuDieses Buch dient als prägnantes Lehrbuch für Studenten in einem fortgeschrittenen Undergraduate- oder First-Year-Graduate-Kurs in verschiedenen Disziplinen wie angewandte Mathematik, Steuerung und Ingenieurwesen, die den modernen Standard der numerischen Methoden von gewöhnlichen und verzögerten Differentialgleichungen verstehen wollen. Experten in denselben Bereichen können sich auch über die jüngsten Entwicklungen in der numerischen Analyse solcher Differentialsysteme informieren. Gewöhnliche Differentialgleichungen (ODEs) sind ein starkes mathematisches Werkzeug, um eine Vielzahl von Phänomenen in Wissenschaft und Technik auszudrücken. Neben ihrer eigenen Bedeutung ist eine der mächtigen Richtungen, in die sich ODEs ausdehnen, die Einbeziehung einer unbekannten Funktion mit verzögertem Argument. Dies wird als verzögerte Differentialgleichungen (Delay differential equations, DDEs) bezeichnet, die häufig in der mathematischen Modellierung vonBiologie, Demographie, Epidemiologie und Kontrolltheorie vorkommen. In einigen Fällen kann die Lösung einer Differentialgleichung durch algebraische Kombinationen bekannter mathematischer Funktionen erhalten werden. In vielen praktischen Fällen ist eine solche Lösung jedoch recht schwierig oder nicht verfügbar, und es sind numerische Näherungen erforderlich. Die moderne Entwicklung von Computern beschleunigt die Situation und eröffnet darüber hinaus mehr Möglichkeiten der numerischen Mittel. Die Kenntnis und das Fachwissen über die numerische Lösung von Differentialgleichungen wird nun in weiten Bereichen der Wissenschaft und des Ingenieurwesens vorausgesetzt.Man könnte meinen, dass ein gut organisiertes Softwarepaket wie MATLAB in etwa die gleiche Lösung bietet. In gewisser Weise stimmt das auch, aber man muss bedenken, dass der blinde Einsatz von Softwarepaketen den Benutzer in die Irre führt. Das Wesentliche der numerischen Lösung von Differentialgleichungen muss noch gelernt werden. Das vorliegende Buch soll das Wesentliche der numerischen Lösungen von gewöhnlichen Differentialgleichungen sowie von Verzögerungsdifferentialgleichungen vermitteln. Die Autoren haben insbesondere festgestellt, dass es noch wenige prägnante Lehrbücher über Verzögerungsdifferentialgleichungen gibt, und haben sich dann daran gemacht, die Lücke durch möglichst transparente Beschreibungen zu schließen. Die wichtigsten Algorithmen zur numerischen Lösung sind in diesem Buch klar beschrieben. Auch die Stabilität von Lösungen von ODEs und DDEs ist von entscheidender Bedeutung. Das Buch führt in die asymptotische Stabilität von analytischen und numerischen Lösungen ein und bietet einen praktischen Weg zur Analyse ihrer Stabilität unter Verwendung einer Theorie komplexer Funktionen.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part III (Lecture Notes in Computer Science #14449)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part IV (Lecture Notes in Computer Science #14450)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part V (Lecture Notes in Computer Science #14451)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part VI (Lecture Notes in Computer Science #14452)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14447)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part II (Lecture Notes in Computer Science #14448)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Molecular Techniques for Studying Viruses: Practical Notes
by Zubaida Hassan Gulfaraz KhanThis volume provides detailed information on various laboratory techniques and methodologies used for studying viruses at the molecular level. It covers essential topics such as nucleic acid isolation, protein isolation, PCR-based techniques, western blotting, serological assays, immunoprecipitation, small interfering RNA (siRNA), histological methods, bioinformatics and in silico simulations. Each chapter provides a detailed overview of the techniques, their applications, and their significance in virus research. The book is a useful resource as a practical introductory note that could be used for hands-on training of students, both undergraduates and junior postgraduates.
Frontiers in Genetics Algorithm Theory and Applications (Springer Tracts in Nature-Inspired Computing)
by Mahdi Khosravy Neeraj Gupta Olaf WitkowskiThis book reviews recent advances in theory and applications of genetic algorithm (GA). The book is composed of five parts; Part 1 of the book involves the chapters about the advances in GA theory. Part 2 concerns applications in health, society, and economy. Part 3 has an inclusive focus on application in power systems, and Part 4 concerns the applications of GA in electrical vehicle industries. Finally, Part 5 includes applications in signal and image processing.
Digital Transformation: Industry 4.0 to Society 5.0 (Disruptive Technologies and Digital Transformations for Society 5.0)
by Avadhesh Kumar Shrddha Sagar Poongodi Thangamuthu B. BalamuruganThis book focuses on computing for Industry 4.0 illustrating different domains with the purpose of integration with existing domains for automation of processes. It gives readers an idea about the various challenges and design structure for computing of Industry 4.0. The contents include contributions from experts in Cyber-Physical Systems (CPS), the Internet of Things (IoT), Industrial Internet of Things (IIoT), cloud computing, cognitive computing, and artificial intelligence across the world, contributing their knowledge to identify the different characteristics of the above domains.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part VII (Communications in Computer and Information Science #1961)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part VIII (Communications in Computer and Information Science #1962)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part IX (Communications in Computer and Information Science #1963)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part X (Communications in Computer and Information Science #1964)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XI (Communications in Computer and Information Science #1965)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XII (Communications in Computer and Information Science #1966)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XIII (Communications in Computer and Information Science #1967)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XIV (Communications in Computer and Information Science #1968)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XV (Communications in Computer and Information Science #1969)
by Biao Luo Long Cheng Zheng-Guang Wu Hongyi Li Chaojie LiThe nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Association Analysis Techniques and Applications in Bioinformatics
by Qingfeng ChenAdvances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis. This book offers an essential introduction to the theoretical and practical aspects of association analysis, including data pre-processing, data mining methods/algorithms, and tools that are widely applied for computational biology. It covers significant recent advances in the field, both foundational and application-oriented, helping readers understand the basic principles and emerging techniques used to discover interesting association patterns in diverse and heterogeneous biology data, such as structure-function correlations, and complex networks with gene/protein regulation. The main results and approaches are described in an easy-to-follow way and accompanied by sufficientreferences and suggestions for future research. This carefully edited monograph is intended to provide investigators in the fields of data mining, machine learning, artificial intelligence, and bioinformatics with a profound guide to the role of association analysis in computational biology. It is also very useful as a general source of information on association analysis, and as an overall accompanying course book and self-study material for graduate students and researchers in both computer science and bioinformatics.
Stochastic Approximation: A Dynamical Systems Viewpoint (Texts and Readings in Mathematics #48)
by Vivek S. BorkarThis book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.