Автор: Cormen, Thomas H. Название: Introduction to Algorithms 4E ISBN: 026204630X ISBN-13(EAN): 9780262046305 Издательство: MIT Press Рейтинг: Цена: 169290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A comprehensive update of a widely used textbook, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Since the publication of the first edition, Introduction to Algorithms has become a widely used text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout, with new chapters on matchings in bipartite graphs, online algorithms, and machine learning, and new material on such topics as solving recurrence equations, hash tables, potential functions, and suffix arrays. Each chapter is relatively self-contained, presenting an algorithm, a design technique, an application area, or a related topic, and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The fourth edition has 140 new exercises and 22 new problems, and color has been added to improve visual presentations. The writing has been revised throughout, and made clearer, more personal, and gender neutral. The book's website offers supplemental material.
A riveting account of espionage for the digital age, from one of America's leading intelligence experts
Spying has never been more ubiquitous-or less understood. The world is drowning in spy movies, TV shows, and novels, but universities offer more courses on rock and roll than on the CIA and there are more congressional experts on powdered milk than espionage. This crisis in intelligence education is distorting public opinion, fueling conspiracy theories, and hurting intelligence policy. In Spies, Lies, and Algorithms, Amy Zegart separates fact from fiction as she offers an engaging and enlightening account of the past, present, and future of American espionage as it faces a revolution driven by digital technology. Drawing on decades of research and hundreds of interviews with intelligence officials, Zegart provides a history of U.S. espionage, from George Washington's Revolutionary War spies to today's spy satellites; examines how fictional spies are influencing real officials; gives an overview of intelligence basics and life inside America's intelligence agencies; explains the deadly cognitive biases that can mislead analysts; and explores the vexed issues of traitors, covert action, and congressional oversight. Most of all, Zegart describes how technology is empowering new enemies and opportunities, and creating powerful new players, such as private citizens who are successfully tracking nuclear threats using little more than Google Earth. And she shows why cyberspace is, in many ways, the ultimate cloak-and-dagger battleground, where nefarious actors employ deception, subterfuge, and advanced technology for theft, espionage, and information warfare. A fascinating and revealing account of espionage for the digital age, Spies, Lies, and Algorithms is essential reading for anyone who wants to understand the reality of spying today.
Автор: Cormen, Thomas H., E Название: Introduction to algorithms 3 ed. ISBN: 0262033844 ISBN-13(EAN): 9780262033848 Издательство: MIT Press Рейтинг: Цена: 183920.00 T Наличие на складе: Нет в наличии. Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.
Автор: Corke, Peter Название: Robotics, Vision and Control, 2 ed. ISBN: 3319544128 ISBN-13(EAN): 9783319544120 Издательство: Springer Рейтинг: Цена: 0.00 T Наличие на складе: Невозможна поставка. Описание: Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together.
Автор: Sujatha R., Aarthy S. L., Vettriselvan R. Название: Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics ISBN: 0367466635 ISBN-13(EAN): 9780367466633 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems.
Автор: Roughgarden Tim Название: Algorithms Illuminated, Part 1: The Basics ISBN: 0999282905 ISBN-13(EAN): 9780999282908 Издательство: Неизвестно Цена: 18380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides a conceptual approach that will encourage students learning algebra to employ a variety of thinking processes and strategies and, most importantly, will enable them to truly understand the concepts that underlie the problems they are solving. The book includes tasks focusing on algebraic expressions, equations, and functions, followed by tasks that integrate several mathematical concepts.
Автор: Roughgarden, Tim Название: Algorithms illuminated (part 2) ISBN: 0999282921 ISBN-13(EAN): 9780999282922 Издательство: Неизвестно Рейтинг: Цена: 18380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and machine learning. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject for anyone with at least a little programming experience. The exposition emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details---like a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. Part 2 covers graph search and applications, shortest paths, and the usage and implementation of several data structures (heaps, search trees, hash tables, and bloom filters).
Автор: Kochenderfer Mykel J., Wheeler Tim A. Название: Algorithms for Optimization ISBN: 0262039427 ISBN-13(EAN): 9780262039420 Издательство: MIT Press Рейтинг: Цена: 95930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.
This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language.
Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.
Автор: Roughgarden Tim Название: Algorithms Illuminated (Part 3): Greedy Algorithms and Dynamic Programming ISBN: 0999282948 ISBN-13(EAN): 9780999282946 Издательство: Неизвестно Рейтинг: Цена: 18380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).
Автор: Chattamvelli Rajan, Shanmugam Ramalingam Название: Generating Functions in Engineering and the Applied Sciences ISBN: 1681736381 ISBN-13(EAN): 9781681736389 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 46200.00 T Наличие на складе: Нет в наличии. Описание:
This is an introductory book on generating functions (GFs) and their applications.
It discusses commonly encountered generating functions in engineering and applied sciences, such as ordinary generating functions (OGF), exponential generating functions (EGF), probability generating functions (PGF), etc. Some new GFs like Pochhammer generating functions for both rising and falling factorials are introduced in Chapter 2. Two novel GFs called "mean deviation generating function" (MDGF) and "survival function generating function" (SFGF), are introduced in Chapter 3. The mean deviation of a variety of discrete distributions are derived using the MDGF. The last chapter discusses a large number of applications in various disciplines including algebra, analysis of algorithms, polymer chemistry, combinatorics, graph theory, number theory, reliability, epidemiology, bio-informatics, genetics, management, economics, and statistics.
Some background knowledge on GFs is often assumed for courses in analysis of algorithms, advanced data structures, digital signal processing (DSP), graph theory, etc. These are usually provided by either a course on "discrete mathematics" or "introduction to combinatorics." But, GFs are also used in automata theory, bio-informatics, differential equations, DSP, number theory, physical chemistry, reliability engineering, stochastic processes, and so on. Students of these courses may not have exposure to discrete mathematics or combinatorics. This book is written in such a way that even those who do not have prior knowledge can easily follow through the chapters, and apply the lessons learned in their respective disciplines. The purpose is to give a broad exposure to commonly used techniques of combinatorial mathematics, highlighting applications in a variety of disciplines.
Название: Sequential and Parallel Algorithms and Data Structures ISBN: 3030252086 ISBN-13(EAN): 9783030252083 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This undergraduate textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems.
Credit Data and Scoring: The First Triumph of Big Data and Big Algorithms illuminates the often-hidden practice of predicting an individual's economic responsibility. Written by a leading practitioner, it examines the international implications of US leadership in credit scoring and what other countries have learned from it in building their own systems. Through its comprehensive contemporary perspective, the book also explores how algorithms and big data are driving the future of credit scoring. By revealing a new big picture and data comparisons, it delivers useful insights into legal, regulatory and data manipulation.
Provides insights into credit scoring goals and methods
Examines U.S leadership in developing credit data and algorithms and how other countries depart from it
Analyzes the growing influence of algorithms in data scoring
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