Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne We motivate each algorithm that we address by examining its impact on applications to science, engineering, and industry The textbook is organized into six chapters: Chapter 1: Fundamentals introduces a scientific and engineering basis for comparing algorithms and making predictions It also includes our programming model
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Lecture Slides - Princeton University This page provides information about online lectures and lecture slides for use in teaching and learning from the book Algorithms, 4 e These lectures are appropriate for use by instructors as the basis for a “flipped” class on the subject, or for self-study by individuals Flipped classroom
Algorithms by Jeff Erickson - University of Illinois Urbana-Champaign This web page contains a free electronic version of my self-published textbook Algorithms, along with other lecture notes I have written for various theoretical computer science classes at the University of Illinois, Urbana-Champaign since 1998 Publication
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Introduction to Algorithms | Electrical Engineering and Computer . . . This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques …
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Algorithms: Design and Analysis, Part 1 - Stanford Online In this course you will learn several fundamental principles of algorithm design You'll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication You'll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths
1. Fundamentals - Princeton University The objective of this book is to study a broad variety of important and useful algorithms —methods for solving problems that are suited for computer implementations Algorithms go hand in hand with data structures —schemes for organizing data This chapter introduces the basic tools that we need to study algorithms and data structures
4. Graphs - Princeton University We progress through the four most important types of graph models: undirected graphs (with simple connections), digraphs graphs (where the direction of each connection is significant), edge-weighted graphs (where each connection has an software associated weight), and edge-weighted digraphs (where each connection has both a direction and a weight)
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Introduction to Algorithms - MIT Press 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, with self-contained chapters and algorithms in pseudocode
Design and Analysis of Algorithms - MIT OpenCourseWare This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography