Download or read book Network Algorithmics written by George Varghese and published by Morgan Kaufmann. This book was released on 2022-11-11 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network Algorithmics: An Interdisciplinary Approach to Designing Fast Networked Devices, Second Edition takes an interdisciplinary approach to applying principles for efficient implementation of network devices, offering solutions to the problem of network implementation bottlenecks. In designing a network device, there are dozens of decisions that affect the speed with which it will perform – sometimes for better, but sometimes for worse. The book provides a complete and coherent methodology for maximizing speed while meeting network design goals. The book is uniquely focused on the seamless integration of data structures, algorithms, operating systems and hardware/software co-designs for high-performance routers/switches and network end systems. Thoroughly updated based on courses taught by the authors over the past decade, the book lays out the bottlenecks most often encountered at four disparate levels of implementation: protocol, OS, hardware and architecture. It then develops fifteen principles key to breaking these bottlenecks, systematically applying them to bottlenecks found in end-nodes, interconnect devices and specialty functions located along the network. Later sections discuss the inherent challenges of modern cloud computing and data center networking. Offers techniques that address common bottlenecks of interconnect devices, including routers, bridges, gateways, endnodes, and Web servers Presents many practical algorithmic concepts that students and readers can work with immediately Revised and updated throughout to discuss the latest developments from authors’ courses, including measurement algorithmics, randomization, regular expression matching, and software-defined networking Includes a new, rich set of homework exercises and exam questions to facilitate classroom use

Download or read book Algorithmics written by Gilles Brassard and published by Englewood Cliffs, N.J. : Prentice Hall. This book was released on 1988 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Guide to Experimental Algorithmics written by Catherine C. McGeoch and published by Cambridge University Press. This book was released on 2012-01-30 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.

Download or read book Algorithmics of Matching Under Preferences written by David F. Manlove and published by World Scientific. This book was released on 2013 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matching problems with preferences are all around us OCo they arise when agents seek to be allocated to one another on the basis of ranked preferences over potential outcomes. Efficient algorithms are needed for producing matchings that optimise the satisfaction of the agents according to their preference lists.In recent years there has been a sharp increase in the study of algorithmic aspects of matching problems with preferences, partly reflecting the growing number of applications of these problems worldwide. This book describes the most important results in this area, providing a timely update to The Stable Marriage Problem: Structure and Algorithms (D Gusfield and R W Irving, MIT Press, 1989) in connection with stable matching problems, whilst also broadening the scope to include matching problems with preferences under a range of alternative optimality criteria."

Download or read book Algorithmic Puzzles written by Anany Levitin and published by OUP USA. This book was released on 2011-10-14 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic puzzles are puzzles involving well-defined procedures for solving problems. This book will provide an enjoyable and accessible introduction to algorithmic puzzles that will develop the reader's algorithmic thinking. The first part of this book is a tutorial on algorithm design strategies and analysis techniques. Algorithm design strategies — exhaustive search, backtracking, divide-and-conquer and a few others — are general approaches to designing step-by-step instructions for solving problems. Analysis techniques are methods for investigating such procedures to answer questions about the ultimate result of the procedure or how many steps are executed before the procedure stops. The discussion is an elementary level, with puzzle examples, and requires neither programming nor mathematics beyond a secondary school level. Thus, the tutorial provides a gentle and entertaining introduction to main ideas in high-level algorithmic problem solving. The second and main part of the book contains 150 puzzles, from centuries-old classics to newcomers often asked during job interviews at computing, engineering, and financial companies. The puzzles are divided into three groups by their difficulty levels. The first fifty puzzles in the Easier Puzzles section require only middle school mathematics. The sixty puzzle of average difficulty and forty harder puzzles require just high school mathematics plus a few topics such as binary numbers and simple recurrences, which are reviewed in the tutorial. All the puzzles are provided with hints, detailed solutions, and brief comments. The comments deal with the puzzle origins and design or analysis techniques used in the solution. The book should be of interest to puzzle lovers, students and teachers of algorithm courses, and persons expecting to be given puzzles during job interviews.

Download or read book The Oxford Handbook of Algorithmic Music written by Alex McLean and published by Oxford University Press. This book was released on 2018-01-18 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the ongoing development of algorithmic composition programs and communities of practice expanding, algorithmic music faces a turning point. Joining dozens of emerging and established scholars alongside leading practitioners in the field, chapters in this Handbook both describe the state of algorithmic composition and also set the agenda for critical research on and analysis of algorithmic music. Organized into four sections, chapters explore the music's history, utility, community, politics, and potential for mass consumption. Contributors address such issues as the role of algorithms as co-performers, live coding practices, and discussions of the algorithmic culture as it currently exists and what it can potentially contribute society, education, and ecommerce. Chapters engage particularly with post-human perspectives - what new musics are now being found through algorithmic means which humans could not otherwise have made - and, in reciprocation, how algorithmic music is being assimilated back into human culture and what meanings it subsequently takes. Blending technical, artistic, cultural, and scientific viewpoints, this Handbook positions algorithmic music making as an essentially human activity.

Download or read book Algorithmic Thinking written by Daniel Zingaro and published by No Starch Press. This book was released on 2020-12-15 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, problem-based introduction to building algorithms and data structures to solve problems with a computer. Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems. Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like: The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations The union-find data structure to answer questions about connections in a social network or determine who are friends or enemies The heap data structure to determine the amount of money given away in a promotion The hash-table data structure to determine whether snowflakes are unique or identify compound words in a dictionary NOTE: Each problem in this book is available on a programming-judge website. You'll find the site's URL and problem ID in the description. What's better than a free correctness check?

Download or read book ReCombinatorics written by Dan Gusfield and published by MIT Press. This book was released on 2014-07-03 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: When a Philadelphia girl intercepts a message about an impending British attack against her father's regiment, commanded by General Washington, in White Marsh, she travels alone by horseback to warn the Patriot army.

Download or read book Algorithms of Oppression written by Safiya Umoja Noble and published by NYU Press. This book was released on 2018-02-20 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acknowledgments -- Introduction: the power of algorithms -- A society, searching -- Searching for Black girls -- Searching for people and communities -- Searching for protections from search engines -- The future of knowledge in the public -- The future of information culture -- Conclusion: algorithms of oppression -- Epilogue -- Notes -- Bibliography -- Index -- About the author

Download or read book Advancing Research in Information and Communication Technology written by Michael Goedicke and published by Springer Nature. This book was released on 2021-08-03 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: For 60 years the International Federation for Information Processing (IFIP) has been advancing research in Information and Communication Technology (ICT). This book looks into both past experiences and future perspectives using the core of IFIP's competence, its Technical Committees (TCs) and Working Groups (WGs). Soon after IFIP was founded, it established TCs and related WGs to foster the exchange and development of the scientific and technical aspects of information processing. IFIP TCs are as diverse as the different aspects of information processing, but they share the following aims: To establish and maintain liaison with national and international organizations with allied interests and to foster cooperative action, collaborative research, and information exchange. To identify subjects and priorities for research, to stimulate theoretical work on fundamental issues, and to foster fundamental research which will underpin future development. To provide a forum for professionals with a view to promoting the study, collection, exchange, and dissemination of ideas, information, and research findings and thereby to promote the state of the art. To seek and use the most effective ways of disseminating information about IFIP’s work including the organization of conferences, workshops and symposia and the timely production of relevant publications. To have special regard for the needs of developing countries and to seek practicable ways of working with them. To encourage communication and to promote interaction between users, practitioners, and researchers. To foster interdisciplinary work and – in particular – to collaborate with other Technical Committees and Working Groups. The 17 contributions in this book describe the scientific, technical, and further work in TCs and WGs and in many cases also assess the future consequences of the work’s results. These contributions explore the developments of IFIP and the ICT profession now and over the next 60 years. The contributions are arranged per TC and conclude with the chapter on the IFIP code of ethics and conduct.

Download or read book Algorithmic Number Theory Efficient algorithms written by Eric Bach and published by MIT Press. This book was released on 1996 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 1.

Download or read book Experimental Algorithmics written by Rudolf Fleischer and published by Springer. This book was released on 2003-07-01 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.

Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.

Download or read book Twenty Lectures on Algorithmic Game Theory written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2016-08-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.

Download or read book Algorithmic Antitrust written by Aurelien Portuese and published by Springer Nature. This book was released on 2022-01-21 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are ubiquitous in our daily lives. They affect the way we shop, interact, and make exchanges on the marketplace. In this regard, algorithms can also shape competition on the marketplace. Companies employ algorithms as technologically innovative tools in an effort to edge out competitors. Antitrust agencies have increasingly recognized the competitive benefits, but also competitive risks that algorithms entail. Over the last few years, many algorithm-driven companies in the digital economy have been investigated, prosecuted and fined, mostly for allegedly unfair algorithm design. Legislative proposals aim at regulating the way algorithms shape competition. Consequently, a so-called “algorithmic antitrust” theory and practice have also emerged. This book provides a more innovation-driven perspective on the way antitrust agencies should approach algorithmic antitrust. To date, the analysis of algorithmic antitrust has predominantly been shaped by pessimistic approaches to the risks of algorithms on the competitive environment. With the benefit of the lessons learned over the last few years, this book assesses whether these risks have actually materialized and whether antitrust laws need to be adapted accordingly. Effective algorithmic antitrust requires to adequately assess the pro- and anti-competitive effects of algorithms on the basis of concrete evidence and innovation-related concerns. With a particular emphasis on the European perspective, this book brings together experts and scrutinizes on the implications of algorithmic antitrust for regulation and innovation.

Download or read book Algorithmics for VLSI written by C. Trullemans and published by . This book was released on 1986 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Reading Machines written by Stephen Ramsay and published by University of Illinois Press. This book was released on 2011-12-01 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Besides familiar and now-commonplace tasks that computers do all the time, what else are they capable of? Stephen Ramsay's intriguing study of computational text analysis examines how computers can be used as "reading machines" to open up entirely new possibilities for literary critics. Computer-based text analysis has been employed for the past several decades as a way of searching, collating, and indexing texts. Despite this, the digital revolution has not penetrated the core activity of literary studies: interpretive analysis of written texts. Computers can handle vast amounts of data, allowing for the comparison of texts in ways that were previously too overwhelming for individuals, but they may also assist in enhancing the entirely necessary role of subjectivity in critical interpretation. Reading Machines discusses the importance of this new form of text analysis conducted with the assistance of computers. Ramsay suggests that the rigidity of computation can be enlisted in the project of intuition, subjectivity, and play.