Braverman Readings In Machine Learning Key Ideas From Inception To Current State

Author : Lev Rozonoer,Boris Mirkin,Ilya Muchnik
Publisher : Springer
Page : 361 pages
File Size : 49,5 Mb
Release : 2018-08-30
Category : Computers
ISBN : 9783319994925

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Braverman Readings in Machine Learning. Key Ideas from Inception to Current State by Lev Rozonoer,Boris Mirkin,Ilya Muchnik Pdf

This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing machine learning theory. The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches. The collection is divided in three parts. The first part bridges the past and the present and covers the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning. The third part includes short essays by a friend, a student, and a colleague.

Author : Khosrow-Pour D.B.A., Mehdi
Publisher : IGI Global
Page : 2734 pages
File Size : 44,9 Mb
Release : 2020-09-29
Category : Business & Economics
ISBN : 9781799834748

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Encyclopedia of Organizational Knowledge, Administration, and Technology by Khosrow-Pour D.B.A., Mehdi Pdf

For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.

Author : Shady S. Refaat,Omar Ellabban,Sertac Bayhan,Haitham Abu-Rub,Frede Blaabjerg,Miroslav M. Begovic
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 40,6 Mb
Release : 2021-07-27
Category : Science
ISBN : 9781119422457

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Smart Grid and Enabling Technologies by Shady S. Refaat,Omar Ellabban,Sertac Bayhan,Haitham Abu-Rub,Frede Blaabjerg,Miroslav M. Begovic Pdf

SMART GRID AND ENABLING TECHNOLOGIES Discover foundational topics in smart grid technology as well as an exploration of the current and future state of the industry As the relationship between fossil fuel use and climate change becomes ever clearer, the search is on for reliable, renewable and less harmful sources of energy. Sometimes called the “electronet” or the “energy Internet,” smart grids promise to integrate renewable energy, information, and communication technologies with the existing electrical grid and deliver electricity more efficiently and reliably. Smart Grid and Enabling Technologies delivers a complete vision of smart grid technology and applications, including foundational and fundamental technologies, the technology that enables smart grids, the current state of the industry, and future trends in smart energy. The book offers readers thorough discussions of modern smart grid technology, including advanced metering infrastructure, net zero energy buildings, and communication, data management, and networks in smart grids. The accomplished authors also discuss critical challenges and barriers facing the smart grid industry as well as trends likely to be of importance in its future development. Readers will also benefit from the inclusion of: A thorough introduction to smart grid architecture, including traditional grids, the fundamentals of electric power, definitions and classifications of smart grids, and the components of smart grid technology An exploration of the opportunities and challenges posed by renewable energy integration Practical discussions of power electronics in the smart grid, including power electronics converters for distributed generation, flexible alternating current transmission systems, and high voltage direct current transmission systems An analysis of distributed generation Perfect for scientists, researchers, engineers, graduate students, and senior undergraduate students studying and working with electrical power systems and communication systems. Smart Grid and Enabling Technologies will also earn a place in the libraries of economists, government planners and regulators, policy makers, and energy stakeholders working in the smart grid field.

Author : George Bebis,Takis Benos,Ken Chen,Katharina Jahn,Ernesto Lima
Publisher : Springer Nature
Page : 99 pages
File Size : 52,6 Mb
Release : 2019-11-14
Category : Computers
ISBN : 9783030352103

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Mathematical and Computational Oncology by George Bebis,Takis Benos,Ken Chen,Katharina Jahn,Ernesto Lima Pdf

This book constitutes the refereed proceedings of the First International Symposium on Mathematical and Computational Oncology, ISMCO'2019, held in Lake Tahoe, NV, USA, in October 2019. The 7 full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections named: Tumor evolvability and intra-tumor heterogeneity; Imaging and scientific visualization for cancer research; Statistical methods and data mining for cancer research (SMDM); Spatio-temporal tumor modeling and simulation (STTMS).

Author : Nga Thi Hong Nguyen,Shivani Agarwal,Ewa Ziemba
Publisher : CRC Press
Page : 397 pages
File Size : 52,5 Mb
Release : 2023-12-13
Category : Technology & Engineering
ISBN : 9781003808589

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Analytics in Finance and Risk Management by Nga Thi Hong Nguyen,Shivani Agarwal,Ewa Ziemba Pdf

This book presents contemporary issues and challenges in finance and risk management in a time of rapid transformation due to technological advancements. It includes research articles based on financial and economic data and intends to cover the emerging role of analytics in financial management, asset management, and risk management. Analytics in Finance and Risk Management covers statistical techniques for data analysis in finance It explores applications in finance and risk management, covering empirical properties of financial systems. It addresses data science involving the study of statistical and computational models and includes basic and advanced concepts. The chapters incorporate the latest methodologies and challenges facing financial and risk management and illustrate related issues and their implications in the real world. The primary users of this book will include researchers, academicians, postgraduate students, professionals in engineering and business analytics, managers, consultants, and advisors in IT firms, financial markets, and services domains.

Author : Vladimir Vovk,Alexander Gammerman,Glenn Shafer
Publisher : Springer Nature
Page : 490 pages
File Size : 50,6 Mb
Release : 2022-12-13
Category : Computers
ISBN : 9783031066498

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Algorithmic Learning in a Random World by Vladimir Vovk,Alexander Gammerman,Glenn Shafer Pdf

This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature of conformal prediction is the principled treatment of the reliability of predictions. The prediction algorithms described — conformal predictors — are provably valid in the sense that they evaluate the reliability of their own predictions in a way that is neither over-pessimistic nor over-optimistic (the latter being especially dangerous). The approach is still flexible enough to incorporate most of the existing powerful methods of machine learning. The book covers both key conformal predictors and the mathematical analysis of their properties. Algorithmic Learning in a Random World contains, in addition to proofs of validity, results about the efficiency of conformal predictors. The only assumption required for validity is that of "randomness" (the prediction algorithm is presented with independent and identically distributed examples); in later chapters, even the assumption of randomness is significantly relaxed. Interesting results about efficiency are established both under randomness and under stronger assumptions. Since publication of the First Edition in 2005 conformal prediction has found numerous applications in medicine and industry, and is becoming a popular machine-learning technique. This Second Edition contains three new chapters. One is about conformal predictive distributions, which are more informative than the set predictions produced by standard conformal predictors. Another is about the efficiency of ways of testing the assumption of randomness based on conformal prediction. The third new chapter harnesses conformal testing procedures for protecting machine-learning algorithms against changes in the distribution of the data. In addition, the existing chapters have been revised, updated, and expanded.

Author : José Bravo
Publisher : Springer Nature
Page : 350 pages
File Size : 50,6 Mb
Release : 2024-07-01
Category : Electronic
ISBN : 9783031483066

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Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023) by José Bravo Pdf

Author : James Berger,Xiao-Li Meng,Nancy Reid,Min-ge Xie
Publisher : CRC Press
Page : 421 pages
File Size : 52,7 Mb
Release : 2024-02-26
Category : Mathematics
ISBN : 9781003837640

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Handbook of Bayesian, Fiducial, and Frequentist Inference by James Berger,Xiao-Li Meng,Nancy Reid,Min-ge Xie Pdf

The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the foundations of statistical inference can sometimes lead to different interpretations and conclusions from the same dataset. The increased interest in the foundations of statistical inference has led to many publications, and recent vibrant research activities in statistics, applied mathematics, philosophy and other fields of science reflect the importance of this development. The BFF approaches not only bridge foundations and scientific learning, but also facilitate objective and replicable scientific research, and provide scalable computing methodologies for the analysis of big data. Most of the published work typically focusses on a single topic or theme, and the body of work is scattered in different journals. This handbook provides a comprehensive introduction and broad overview of the key developments in the BFF schools of inference. It is intended for researchers and students who wish for an overview of foundations of inference from the BFF perspective and provides a general reference for BFF inference. Key Features: Provides a comprehensive introduction to the key developments in the BFF schools of inference Gives an overview of modern inferential methods, allowing scientists in other fields to expand their knowledge Is accessible for readers with different perspectives and backgrounds

Author : Boris Goldengorin,Sergei Kuznetsov
Publisher : Springer Nature
Page : 447 pages
File Size : 54,7 Mb
Release : 2023-09-23
Category : Computers
ISBN : 9783031316548

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Data Analysis and Optimization by Boris Goldengorin,Sergei Kuznetsov Pdf

This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with automated methods to analyze patterns and models for various types of data, with applications ranging from scientific discovery to business intelligence and analytics. The book primarily includes exploratory data analysis, pattern mining, clustering, and classification supported by real life case studies. The statistical section of this book explores the impact of data mining and modeling on the predictability assessment of time series. Further new notions of mean values based on ideas of multi-criteria optimization are compared with their conventional definitions, leading to new algorithmic approaches to the calculation of the suggested new means. The style of the written chapters and the provision of a broad yet in-depth overview of data mining, integrating novel concepts from machine learning and statistics, make the book accessible to upper level undergraduate and graduate students in data mining courses. Students and professionals specializing in computer and management science, data mining for high-dimensional data, complex graphs and networks will benefit from the cutting-edge ideas and practically motivated case studies in this book.

Author : Anton A. Buzdin,Ira Ida Skvortsova,Xinmin Li,Ye Wang
Publisher : Frontiers Media SA
Page : 180 pages
File Size : 42,7 Mb
Release : 2021-03-09
Category : Science
ISBN : 9782889665754

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Next Generation Sequencing Based Diagnostic Approaches in Clinical Oncology by Anton A. Buzdin,Ira Ida Skvortsova,Xinmin Li,Ye Wang Pdf

Dr. Anton Buzdin (AB) is employed by Omicsway Corp. (USA). AB received grants from Amazon and Microsoft Azure to support cloud computations. Dr. Xinmin Li is director of JCCC Shared Genomics Resource, the University of California, Los Angeles, CA Dr. Ye Wang is Director of Gene testing Department (Core Lab) of Qingdao Central Hospital, the Second Affiliated Hospital of Qingdao University

Author : Dmitry G. Arseniev,Ludger Overmeyer,Heikki Kälviäinen,Branko Katalinić
Publisher : Springer Nature
Page : 778 pages
File Size : 49,5 Mb
Release : 2019-11-29
Category : Science
ISBN : 9783030349837

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Cyber-Physical Systems and Control by Dmitry G. Arseniev,Ludger Overmeyer,Heikki Kälviäinen,Branko Katalinić Pdf

This book presents the proceedings of the International Conference on Cyber-Physical Systems and Control (CPS&C'2019), held in Peter the Great St. Petersburg Polytechnic University, which is celebrating its 120th anniversary in 2019. The CPS&C'2019 was dedicated to the 35th anniversary of the partnership between Peter the Great St. Petersburg Polytechnic University and Leibniz University of Hannover. Cyber-physical systems (CPSs) are a new generation of control systems and techniques that help promote prospective interdisciplinary research. A wide range of theories and methodologies are currently being investigated and developed in this area to tackle various complex and challenging problems. Accordingly, CPSs represent a scientific and engineering discipline that is set to make an impact on future systems of industrial and social scale that are characterized by the deep integration of real-time processing, sensing, and actuation into logical and physical heterogeneous domains. The CPS&C'2019 brought together researchers and practitioners from all over the world and to discuss cross-cutting fundamental scientific and engineering principles that underline the integration of cyber and physical elements across all application fields. The participants represented research institutions and universities from Austria, Belgium, Bulgaria, China, Finland, Germany, the Netherlands, Russia, Syria, Ukraine, the USA, and Vietnam. These proceedings include 75 papers arranged into five sections, namely keynote papers, fundamentals, applications, technologies, and education and social aspects.

Author : James E. Dobson
Publisher : U of Minnesota Press
Page : 240 pages
File Size : 53,6 Mb
Release : 2023-04-04
Category : Computers
ISBN : 9781452968872

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The Birth of Computer Vision by James E. Dobson Pdf

A revealing genealogy of image-recognition techniques and technologies Today’s most advanced neural networks and sophisticated image-analysis methods come from 1950s and ’60s Cold War culture—and many biases and ways of understanding the world from that era persist along with them. Aerial surveillance and reconnaissance shaped all of the technologies that we now refer to as computer vision, including facial recognition. The Birth of Computer Vision uncovers these histories and finds connections between the algorithms, people, and politics at the core of automating perception today. James E. Dobson reveals how new forms of computerized surveillance systems, high-tech policing, and automated decision-making systems have become entangled, functioning together as a new technological apparatus of social control. Tracing the development of a series of important computer-vision algorithms, he uncovers the ideas, worrisome military origins, and lingering goals reproduced within the code and the products based on it, examining how they became linked to one another and repurposed for domestic and commercial uses. Dobson includes analysis of the Shakey Project, which produced the first semi-autonomous robot, and the impact of student protest in the early 1970s at Stanford University, as well as recovering the computer vision–related aspects of Frank Rosenblatt’s Perceptron as the crucial link between machine learning and computer vision. Motivated by the ongoing use of these major algorithms and methods, The Birth of Computer Vision chronicles the foundations of computer vision and artificial intelligence, its major transformations, and the questionable legacy of its origins. Cover alt text: Two overlapping circles in cream and violet, with black background. Top is a printed circuit with camera eye; below a person at a 1977 computer.

Author : Sanjeevikumar Padmanaban,Sivaraman Palanisamy,Sharmeela Chenniappan,Jens Bo Holm-Nielsen
Publisher : John Wiley & Sons
Page : 404 pages
File Size : 52,5 Mb
Release : 2022-12-20
Category : Science
ISBN : 9781119893967

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Artificial Intelligence-based Smart Power Systems by Sanjeevikumar Padmanaban,Sivaraman Palanisamy,Sharmeela Chenniappan,Jens Bo Holm-Nielsen Pdf

Authoritative resource describing the artificial intelligence and advanced technologies in smart power systems with simulation examples and case studies Artificial Intelligence-based Smart Power Systems presents advanced technologies used in various aspects of smart power systems, especially grid-connected and industrial evolution, covering many new topics such as distribution Phasor management, blockchain technologies for smart power systems, the application of deep learning and reinforced learning, and artificial intelligence techniques. The text also explores the potential consequences of artificial intelligence and advanced technologies in smart power systems in the forthcoming years. To enhance and reinforce learning, the highly qualified editors include many learning resources throughout the text, including MATLAB and HIL codes, end-of-chapter problems, end-of-book solutions, practical examples, and case studies. Artificial Intelligence-based Smart Power Systems includes specific information on topics such as: Modeling and analysis of smart power systems, covering steady state analysis, dynamic analysis, voltage stability, and more Recent advancement in power electronics for smart power systems, covering power electronic converters for renewable energy sources, electric vehicles, and HDVC/FACTs Distribution Phasor Measurement Units (PMU) in smart power systems, covering the need for PMU in distribution and automation of system reconfigurations Power and energy management systems for microgrids Engineering colleges and universities, along with industry research centers, can use the in-depth subject coverage and the extensive supplementary learning resources found in Artificial Intelligence-based Smart Power Systems to gain a holistic understanding of the subject and be able to harness that knowledge within a myriad of practical applications.

Author : Ethem Mining
Publisher : Unknown
Page : 222 pages
File Size : 53,8 Mb
Release : 2019-12-03
Category : Electronic
ISBN : 1671268423

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Machine Learning for Beginners by Ethem Mining Pdf

Are you fascinated about machine learning and AI and you don't know where to start? Have you ever heard people talking about Machine Learning but you only have a vague idea of the actual meaning? Do you want to understand how machine learning could simplify your daily life? Imagine a world where computing systems understand people and the world around us them to a point where they can notice patterns, collect data, interpret it and give recommendations to solve real world problems with high level of precision. It sounds like science fiction but it is happening in healthcare, agriculture, cyber security, facial recognition, targeting and retargeting customers in online advertising, recommending specific products, stories, videos, text etc., self-driving cars, real time pricing, predicting human behavior and much more. Now imagine you being one of the people behind the code; the people who get these advanced systems to work the way they do. Would it be a dream come true for you? By virtue that you are reading this, it is clear that you have some special liking for this advanced tech and would want to learn how you can be one of the people behind the code. Even if not, you probably want to be able to understand the inner workings of these systems. The concept may sound extremely out there and advanced but it won't be if you follow this guide, which takes an easy to follow, beginner friendly language to help you to understand the ins and outs of machine learning! Here is a summary of what this book will teach you: The basics of machine learning, including what it is, how machine learning has evolved over the years, the application of machine learning in today's world and the future of machine learning How machine learning is beneficial in today's world The different approaches to machine learning, including unsupervised, supervised, reinforcement learning method, semi-supervised machine learning and many others The concept of big data analysis, including what is big data, why big data is important, the application of big data in today's world as well as the different data analysis tools that you can use The link between big data and machine learning The different machine learning algorithms, including what machine-learning algorithms are and how and when the different learning algorithms are used The concept of artificial neural networks, including how they work, when to use neural networks and more How decision trees are used in machine learning, including what decision trees are (in respect to machine learning), how they work, how the decision tree is read, the different nodes in decision trees and when to use them The ins and outs of linear and logistic regression in machine learning, including what linear regression is, different types of regression, how linear regression works, how linear regression is used and much more And much more! Even if this is your first encounter with the concept of machine learning, this book will uncover everything you need to know to master machine learning and possibly get started in this field of advanced computing knowing very well what you are venturing into. And the good thing is that the book takes a beginner friendly approach to help you to apply what you learn right away! Would You Like To Know More? Click Buy Now With 1-Click or Buy Now to get started!

Author : Richard S. Sutton,Andrew G. Barto
Publisher : MIT Press
Page : 549 pages
File Size : 43,6 Mb
Release : 2018-11-13
Category : Computers
ISBN : 9780262352703

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Reinforcement Learning, second edition by Richard S. Sutton,Andrew G. Barto Pdf

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.