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Algorithms
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Algorithm and Complexity
This book is about algorithms and complexity, and so it is about methods for solving problems on computers and the costs (usually the running time) of using those methods.
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Algorithms in the Real World: Lecture Notes
This document contains the lecture notes taken by the students in the course Algorithms in the Real World taught at UC Berkeley during the Fall semester, 1997.
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Algorithms for Programmers
This draft is first created to accompany the already established collection of FXT libraries by the same author, on the fast transforms and low level algorithms.
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Design and Analysis of Algorithms: Course Notes
This is a compilation of lecture notes, used by the author to teach CMSC 651: Design and Analysis of Algorithms at Dept. of Computer Science, University of Maryland. This course has been taught several times and each time the coverage of the topics differs slightly.
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Graph-Theoretic Algorithms: Lecture Notes
This document results from the teaching of CS 762: Graph-Theoretic Algorithms at the University of Waterloo in Fall 1999, Winter 2002 and Winter 2004.
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Combinatorial Algorithms
These lecture notes is about algorithms, especially combinatorial algorithms. Put in its basic form, an algorithm is a set of simple, unambiguous, step-by-step instructions for accomplishing a specific task. Note that the word computer doesnt appear anywhere in this definition; algorithms dont necessarily have anything to do with computers. True though, these notes focus (almost) exclusively on algorithms that can be reasonably implemented on a computer. In other words, each step in the algorithm must be something that either is directly supported by a programming language (arithmetic, assignments, loops, recursion, etc.) or is something that the reader already learned how to do in an earlier subjects (sorting, binary search, depth first search, etc.).
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Complexity of Algorithms
The need to be able to measure the complexity of a problem, algorithm or structure, and to obtain bounds and quantitive relations for complexity arises in more and more sciences: besides computer science, the traditional branches of mathematics, statistical physics, biology, medicine, social sciences and engineering are also confronted more and more frequently with this problem. In the approach taken by computer science, complexity is measured by the quantity of computational resources (time, storage, program, communication) used up by a particular task. These notes deal with the foundations of this theory.
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Efficient Algorithms for Sorting and Synchronization
This thesis presents efficient algorithms for internal and external parallel sorting and remote data update. The sorting algorithms approach the problem by concentrating first on highly efficient but incorrect algorithms followed by a cleanup phase that completes the sort.
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Algorithms
This book evolved over the past ten years from a set of lecture notes developed by the authors while teaching the undergraduate Algorithms course at Berkeley and U.C. San Diego.
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