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Algorithms
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course but can be covered in an advanced algorithms cou...
An Introduction to Computational Learning Theory
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the com...
The Foundations of Computability Theory
This book offers an original and informative view of the development of fundamental concepts of computability theory. The treatment is put into historical context, emphasizing the motivation for ideas as well as their logical and formal development. In Part I the author introduces computability theory, with chapters on the foundational crisis of mathematics in the early twentieth century, and formalism. In Part II he explains classical computability theory, with chapters on the quest for formalization, the Turing Machine, and early successes such as defining incomputable problems, c.e. (computably enumerable) sets, and developing methods for proving incomputability. In Part III he explains r...
The Genius of Algorand
In The Genius of Algorand: Technical Elegance and the DeFi Revolution, financier Anthony Scaramucci walks readers through the history of Algorand, from its inception in the mind of an MIT mathematical genius to the current frontline users who are reinventing the way money works. In his usual straight-talking style, Scaramucci explains why the creation of Algorand is so unique and shines a light on the unmet markets where it’s poised to dominate. Along the way, readers will hear the Algorand origin story straight from Silvio Micali, the Italian immigrant who created it. They’ll also meet the slew of current entrepreneurs, BizDev app designers, marketers, and small business owners who are already taking advantage of Algorand’s bright future. Digital currency is already reshaping the global financial markets, but every token is not created equally. In 2021, Scaramucci chose Algorand for his SkyBridge Capital clients. The story of how Scaramucci became an “Algonaut” doubles as a window into the opaque world of financial technology development, and the way visionaries¾from international banks to struggling artists¾are adopting it to change the world.
Indian Americans (Part-I)
Anand G. Mahindra, one of the most successful business men of India Inc., recently added another feather to his cap--Satyam Computer Services Ltd, which was counted as the fourth largest Information Technology (IT) services firm of India until the revelation of a financial fraud by its founder chairman. It was a risk that even the top three Indian IT companies of India avoided, but Anand Mahindra went ahead with the calculated risk of bidding for Satyam that turned out to be--historical and game changer-- in his own words. Venturbay Consultants Pvt Ltd, a subsidiary of Tech Mahindra Ltd., India's sixth largest software exporter outbid the diversified conglomerate Larsen & Toubro Ltd, U.S. ba...
On the Move to Meaningful Internet Systems: OTM 2010
Annotation The two-volume set of LNCS 6426/6427 constitutes the refereed proceedings of 3 confederated international conferences on CoopIS (Cooperative Information Systems), DOA (Distributed Objects and Applications) and ODBASE (Ontologies, DataBases and Applications of SEmantics). These conferences were held in October 2009 in Greece, in Hersonissos on the island of Crete. CoopIS is covering the applications of technologies in an enterprice context as workflow systems and knowledge management. DOA is covering the relevant infrastructure-enabling technologies and finally, OSBASe is covering WEB semantics, XML databases and ontologies. The 83 revised full papers presented together with 3 keyn...
Edge Intelligence
This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container tec...
An Introduction to Computational Learning Theory
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the com...
Machine Learning for Signal Processing
Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.
