The Feel Of Algorithms
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The Feel of Algorithms
Author: Minna Ruckenstein
language: en
Publisher: Univ of California Press
Release Date: 2023-05-23
"This book explores the cultural shift in society that promotes and relies on affectively charged technology relations. Bringing together relatable first-person accounts of what it means to experience algorithms emotionally alongside research developed across anthropology, sociology, media and communication studies, and science and technology studies, The Feel of Algorithms reveals how political-economic processes are felt in the everyday, as we learn about the digital geography of fear and the current lack of collective resources to build algorithmic systems. Minna Ruckenstein builds on the notion that everyday practices are not merely subject to algorithmic logic; rather, people actively respond to and live with data and algorithms, ranging from actual technical operations to their imagined effects. The pleasures, fears, and frustrations come together to produce a blueprint of how such systems should be combined with human aims and efforts. The narrated emotional reactions are not simply individual responses; they tell a more generalizable story of structures of feeling and related attempts to live well with algorithmic systems. The Feel of Algorithms demonstrates that human capacities and aims need active fostering in the algorithmic era. The structures of feeling aid in recognizing troubling practices, but they also call for alternatives that are currently ignored and suppressed"--
Introduction to Algorithms, third edition
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained 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 first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
How to Think About Algorithms
Author: Jeff Edmonds
language: en
Publisher: Cambridge University Press
Release Date: 2008-05-19
This textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.