Mobile Edge Artificial Intelligence PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Mobile Edge Artificial Intelligence PDF full book. Access full book title Mobile Edge Artificial Intelligence by Yuanming Shi. Download full books in PDF and EPUB format.
Author: Yuanming Shi
Publisher: Elsevier
ISBN: 0128238178
Category : Computers
Languages : en
Pages : 206
Get Book Here
Book Description
Front Cover -- Mobile Edge Artificial Intelligence -- Copyright -- Contents -- List of figures -- Biography -- Yuanming Shi -- Kai Yang -- Zhanpeng Yang -- Yong Zhou -- Preface -- Acknowledgments -- Part 1 Introduction and overview -- 1 Motivations and organization -- 1.1 Motivations -- 1.2 Organization -- References -- 2 Primer on artificial intelligence -- 2.1 Basics of machine learning -- 2.1.1 Supervised learning -- 2.1.1.1 Logistic regression -- 2.1.1.2 Support vector machine -- 2.1.1.3 Decision tree -- 2.1.1.4 k-Nearest neighbors method -- 2.1.1.5 Neural network -- 2.1.2 Unsupervised learning -- 2.1.2.1 k-Means algorithm -- 2.1.2.2 Principal component analysis -- 2.1.2.3 Autoencoder -- 2.1.3 Reinforcement learning -- 2.1.3.1 Q-learning -- 2.1.3.2 Policy gradient -- 2.2 Models of deep learning -- 2.2.1 Convolutional neural network -- 2.2.2 Recurrent neural network -- 2.2.3 Graph neural network -- 2.2.4 Generative adversarial network -- 2.3 Summary -- References -- 3 Convex optimization -- 3.1 First-order methods -- 3.1.1 Gradient method for unconstrained problems -- 3.1.2 Gradient method for constrained problems -- 3.1.3 Subgradient descent method -- 3.1.4 Mirror descent method -- 3.1.5 Proximal gradient method -- 3.1.6 Accelerated gradient method -- 3.1.7 Smoothing for nonsmooth optimization -- 3.1.8 Dual and primal-dual methods -- 3.1.9 Alternating direction method of multipliers -- 3.1.10 Stochastic gradient method -- 3.2 Second-order methods -- 3.2.1 Newton's method -- 3.2.2 Quasi-Newton method -- 3.2.3 Gauss-Newton method -- 3.2.4 Natural gradient method -- 3.3 Summary -- References -- 4 Mobile edge AI -- 4.1 Overview -- 4.2 Edge inference -- 4.2.1 On-device inference -- 4.2.2 Edge inference via computation offloading -- 4.2.2.1 Server-based edge inference -- 4.2.2.2 Device-edge joint inference -- 4.3 Edge training.
Author: Yuanming Shi
Publisher: Elsevier
ISBN: 0128238178
Category : Computers
Languages : en
Pages : 206
Get Book Here
Book Description
Front Cover -- Mobile Edge Artificial Intelligence -- Copyright -- Contents -- List of figures -- Biography -- Yuanming Shi -- Kai Yang -- Zhanpeng Yang -- Yong Zhou -- Preface -- Acknowledgments -- Part 1 Introduction and overview -- 1 Motivations and organization -- 1.1 Motivations -- 1.2 Organization -- References -- 2 Primer on artificial intelligence -- 2.1 Basics of machine learning -- 2.1.1 Supervised learning -- 2.1.1.1 Logistic regression -- 2.1.1.2 Support vector machine -- 2.1.1.3 Decision tree -- 2.1.1.4 k-Nearest neighbors method -- 2.1.1.5 Neural network -- 2.1.2 Unsupervised learning -- 2.1.2.1 k-Means algorithm -- 2.1.2.2 Principal component analysis -- 2.1.2.3 Autoencoder -- 2.1.3 Reinforcement learning -- 2.1.3.1 Q-learning -- 2.1.3.2 Policy gradient -- 2.2 Models of deep learning -- 2.2.1 Convolutional neural network -- 2.2.2 Recurrent neural network -- 2.2.3 Graph neural network -- 2.2.4 Generative adversarial network -- 2.3 Summary -- References -- 3 Convex optimization -- 3.1 First-order methods -- 3.1.1 Gradient method for unconstrained problems -- 3.1.2 Gradient method for constrained problems -- 3.1.3 Subgradient descent method -- 3.1.4 Mirror descent method -- 3.1.5 Proximal gradient method -- 3.1.6 Accelerated gradient method -- 3.1.7 Smoothing for nonsmooth optimization -- 3.1.8 Dual and primal-dual methods -- 3.1.9 Alternating direction method of multipliers -- 3.1.10 Stochastic gradient method -- 3.2 Second-order methods -- 3.2.1 Newton's method -- 3.2.2 Quasi-Newton method -- 3.2.3 Gauss-Newton method -- 3.2.4 Natural gradient method -- 3.3 Summary -- References -- 4 Mobile edge AI -- 4.1 Overview -- 4.2 Edge inference -- 4.2.1 On-device inference -- 4.2.2 Edge inference via computation offloading -- 4.2.2.1 Server-based edge inference -- 4.2.2.2 Device-edge joint inference -- 4.3 Edge training.
Author: Xiaofei Wang
Publisher: Springer Nature
ISBN: 9811561869
Category : Computers
Languages : en
Pages : 156
Get Book Here
Book Description
As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.
Author: Michael V. Hayden
Publisher: Penguin
ISBN: 0143109987
Category : Biography & Autobiography
Languages : en
Pages : 466
Get Book Here
Book Description
From the bestselling author of The Assault on Intelligence, an unprecedented high-level master narrative of America's intelligence wars, demonstrating in a time of new threats that espionage and the search for facts are essential to our democracy For General Michael Hayden, playing to the edge means playing so close to the line that you get chalk dust on your cleats. Otherwise, by playing back, you may protect yourself, but you will be less successful in protecting America. "Play to the edge" was Hayden's guiding principle when he ran the National Security Agency, and it remained so when he ran CIA. In his view, many shortsighted and uninformed people are quick to criticize, and this book will give them much to chew on but little easy comfort; it is an unapologetic insider's look told from the perspective of the people who faced awesome responsibilities head on, in the moment. How did American intelligence respond to terrorism, a major war and the most sweeping technological revolution in the last 500 years? What was NSA before 9/11 and how did it change in its aftermath? Why did NSA begin the controversial terrorist surveillance program that included the acquisition of domestic phone records? What else was set in motion during this period that formed the backdrop for the infamous Snowden revelations in 2013? As Director of CIA in the last three years of the Bush administration, Hayden had to deal with the rendition, detention and interrogation program as bequeathed to him by his predecessors. He also had to ramp up the agency to support its role in the targeted killing program that began to dramatically increase in July 2008. This was a time of great crisis at CIA, and some agency veterans have credited Hayden with actually saving the agency. He himself won't go that far, but he freely acknowledges that CIA helped turn the American security establishment into the most effective killing machine in the history of armed conflict. For 10 years, then, General Michael Hayden was a participant in some of the most telling events in the annals of American national security. General Hayden's goals are in writing this book are simple and unwavering: No apologies. No excuses. Just what happened. And why. As he writes, "There is a story here that deserves to be told, without varnish and without spin. My view is my view, and others will certainly have different perspectives, but this view deserves to be told to create as complete a history as possible of these turbulent times. I bear no grudges, or at least not many, but I do want this to be a straightforward and readable history for that slice of the American population who depend on and appreciate intelligence, but who do not have the time to master its many obscure characteristics."
Author: Steven J. Stein
Publisher: John Wiley & Sons
ISBN: 0470681616
Category : Business & Economics
Languages : en
Pages : 375
Get Book Here
Book Description
REVISED AND UPDAT ED WITH NEW RESEARCH INTO EQ AND PERSONAL AND CAREER SUCCESS What is the formula for success at your job? As a spouse? A parent? A Little League baseball coach or behind the bench of a minor hockey team? What does it take to get ahead? To separate yourself from the competition? To lead a less stressful and happier existence? To be fulfilled in personal and professional pursuits? What is the most important dynamic of your makeup? Is it your A) intelligence quotient? or B) emotional quotient? If you picked "A", you are partly correct. Your intelligence quotient can be a predictor of things such as academic achievement. But your IQ is fixed and unchangeable. The real key to personal and professional growth is your emotional intelligence quotient, which you can nurture and develop by learning more about EQ from the international bestseller The EQ Edge. Authors Steven J. Stein and Howard E. Book show you how the dynamic of emotional intelligence works. By understanding EQ, you can build more meaningful relationships, boost your confidence and optimism, and respond to challenges with enthusiasm-all of which are essential ingredients of success. The EQ Edge offers fascinating-and sometimes surprising-insights into what it takes to be a top law-enforcement officer, lawyer, school principal, student, doctor, dentist or CEO. You will learn what the top EQ factors are across many different kinds of jobs, from business managers and customer service representatives to HR professionals and public servants. The EQ Edge will help you determine which personnel are the right fit for job opportunities and who among your staff are the most promising leaders and drivers of your business. And because all of us have other roles-parent, spouse, caregiver to aging parents, neighbor, friend-The EQ Edge also describes how everyone can be more successful in these relationships. "Finally, a practical and usable guide to what emotional intelligence is all about. This book peels the onion on what EQ really is and teaches the reader to assess their own EQ and how to increase it. This is the holy grail for career success."—Michael Feiner, Professor, Columbia Graduate School of Business and author of The Feiner Points of Leadership
Author: Rajiv Pandey
Publisher: Academic Press
ISBN: 0128240555
Category : Science
Languages : en
Pages : 516
Get Book Here
Book Description
Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. - Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing - Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers - Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
Author: Sanjay Misra
Publisher:
ISBN: 9783030808228
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals. Presents fusion of cloud computing services and AI technology for bringing a significant change in the technology industry; Includes self-assessment problems for increasing knowledge of real world problems, i.e., how AI and cloud/edge computing can change business for the better; Provides innovative results of integrations of AI in other applications such as healthcare, finance, manufacturing, transportation, agriculture, etc.
Author: Amir M. Rahmani
Publisher: Springer
ISBN: 9783319576381
Category : Technology & Engineering
Languages : en
Pages : 172
Get Book Here
Book Description
This book describes state-of-the-art approaches to Fog Computing, including the background of innovations achieved in recent years. Coverage includes various aspects of fog computing architectures for Internet of Things, driving reasons, variations and case studies. The authors discuss in detail key topics, such as meeting low latency and real-time requirements of applications, interoperability, federation and heterogeneous computing, energy efficiency and mobility, fog and cloud interplay, geo-distribution and location awareness, and case studies in healthcare and smart space applications.
Author: Katie King
Publisher: Kogan Page Publishers
ISBN: 0749483407
Category : Business & Economics
Languages : en
Pages : 225
Get Book Here
Book Description
Artificial intelligence (AI) is paving the way for the future of marketing and business transformation, yet many organizations struggle to know exactly how and where to integrate it. This book is the ultimate guide to embracing the opportunity that AI can bring for your marketing. With AI forecasted to boost global GDP by 14% by 2030, an efficient and sustainable AI marketing strategy is now essential to avoid losing the competitive edge. Using Artificial Intelligence in Marketing provides the definitive, practical framework needed for marketers to identify, apply and embrace the opportunity to maximize the results and business advancement that AI can bring. Streamlining efficiencies into every business practice, AI automates simpler, repetitive tasks with unrivalled accuracy, allowing sales and marketing teams to return their attention to where human interaction is most valuable: strategy, creativity and personal connection. Using Artificial Intelligence in Marketing outlines key marketing benefits such as accurate market research samples, immediate big data insights and brand-safe content creation, right through to the on-demand customer service that is now expected 24/7. It also explores the inevitable myths, concerns and ethical questions that can arise from the large-scale adoption of AI. This book is an essential read for every 21st century marketer.
Author: Pradip Debnath
Publisher: CRC Press
ISBN: 1000409813
Category : Computers
Languages : en
Pages : 233
Get Book Here
Book Description
Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.
Author: Christian L. Dunis
Publisher: Springer
ISBN: 1137488808
Category : Business & Economics
Languages : en
Pages : 349
Get Book Here
Book Description
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
