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Design And Analysis Of Algorithms by Herbert Edelsbrunner
This book focuses on fundamental data structures and graph algorithms. The emphasis will be on algorithm design and on algorithm analysis.
Author(s): Herbert Edelsbrunner
95 Pages
Data Structures And Algorithms by Sugih Jamin
This note covers the following topics: Algorithm Analysis, algorithmic patterns, Standard I/O and iostream, Foundational Data Structures and Basic Abstract Data Types, Linked-list, Stacks and Queues, PA1 walkthrough, Pointer, Hashing, Recursion and Recurrence Relations, Trees, Binary Search Trees, Range and Multidimensional Searches, Heaps, Tries, Balanced Search Trees, Binary-tree Representations of Multi-way Trees.
Author(s): Sugih Jamin
NA Pages
Distributed Algorithms Lecture Notes
Distributed algorithms are algorithms designed to run on multiple processors, without tight centralized control. Topics covered includes: Variations in model assumptions, Top-level organization is by the timing model, Synchronous model, Asynchronous model, Partially synchronous model, Synchronous networks.
Author(s): Prof. Nancy Lynch
NA Pages
Introduction to Algorithms Lecture Notes
This note concentrates on the design of algorithms and the rigorous analysis of their efficiency. Topics covered includes: the basic definitions of algorithmic complexity, basic tools such as dynamic programming, sorting, searching, and selection; advanced data structures and their applications, graph algorithms and searching techniques such as minimum spanning trees, depth-first search, shortest paths, design of online algorithms and competitive analysis.
Author(s): Michael Dinitz
NA Pages
Design And Analysis Of Algorithms by Herbert Edelsbrunner
This book focuses on fundamental data structures and graph algorithms. The emphasis will be on algorithm design and on algorithm analysis.
Author(s): Herbert Edelsbrunner
95 Pages
Introduction to the Design and Analysis of Algorithms
This note introduces a number of important algorithm design techniques as well as basic algorithms that are interesting both from a theoretical and also practical point of view. Topics covered are: Introduction to Algorithms, Asymptotic Analysis, Recurrence Equations, Sorting Algorithms, Search Trees, Randomized Algorithms and Quicksort, Selection Algorithms, Number Theory and Cryptography Algorithms, Graph algorithms, Greedy Algorithms and External Memory Algorithms.
Author(s): Department of Computer Science at Duke University
NA Pages
Lecture Notes Introduction to Computer Algorithms
This course note provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems.
Author(s): Prof. Erik Demaine, Prof. Ronald Rivest and Prof. Srinivas Devadas
NA Pages
This note covers the following topics: Mathematics for Algorithmic, Greedy Algorithms, Divide and Conquer Algorithms, Dynamic Programming, Amortized Analysis, Hash Table, Binary Search Tree, Graph Algorithms, String Matching, Sorting and Approximate Algorithms
Author(s): Rashid Bin Muhammad
NA Pages
Efficient Algorithms for Sorting and Synchronization (Andrew Tridgell, PDF)
This thesis presents efficient algorithms for internal and external parallel sorting and remote data update. Topics covered includes: Internal Parallel Sorting, External Parallel Sorting, The rsync algorithm, rsync enhancements and optimizations and Further applications for rsync.
Author(s): Andrew Tridgell
115 Pages
Algorithms for Programmers (Jrg Arndt)
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Author(s):
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