This book contains below topics, Recursion, Backtracking, Dynamic Programming, Greedy Algorithms, Basic Graph Algorithms, Depth First Search, Minimum Spanning Trees, Shortest Paths, All Pairs Shortest Paths, Maximum Flows and Minimum Cuts, Applications of Flows and Cuts, NP Hardness.
Author(s): Jeff Erickson, University of Illinois Urbana-Champaign
472 Pages
This book contains below topics, Array based lists, Linked lists, Skiplists, Hash tables, Binary trees, Random binary search trees, Scapegoat trees, Red black trees, Heaps, Sorting algorithms, Graphs, Data structures for integers, External memory searching.
Author(s): Pat Morin, Carleton University
334 Pages
Lecture Notes on Design and Analysis of Algorithms
This note describes the following topics, Greedy methods, Dynamic programming, Backtracking, Branch and bound.
Author(s): Annamalai University
96 Pages
Lecture Notes On Design And Analysis Of Algorithms
This note covers the following topics, Design and analysis of algorithms, Growth of Functions, Recurrences, Solution of Recurrences by substitution, Recursion tree method, Master Method, Worst case analysis of merge sort, quick sort and binary search, Design and analysis of Divide and Conquer Algorithms, Heaps and Heap sort, Priority Queue, Lower Bounds for Sorting, Dynamic Programming algorithms, Matrix Chain Multiplication, Elements of Dynamic Programming, Longest Common Subsequence, Greedy Algorithms, Activity Selection Problem, Elements of Greedy Strategy, Fractional Knapsack Problem, Huffman Codes, Graph Algorithm BFS and DFS, Minimum Spanning Trees, Kruskal algorithm, Prims Algorithm, Fourier transforms and RabinKarp Algorithm.
Author(s): Dr. Subasish Mohapatra
125 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
Advanced Algorithms Lectures by Shuchi Chawla
Advanced Algorithms Lectures by Shuchi Chawla give an insight into advanced techniques in the design and analysis of algorithms. The lectures cover topics such as greedy algorithms, dynamic programming, and network flow applications. Advanced topics, including randomized algorithms and Kargers mincut algorithm, NPcompleteness, together with linear programming, primaldual algorithms, and semidefinite programming, are discussed. Chawla also deals with models like Probably Approximately Correct PAC and boosting within this framework. This set of lectures comprehensively covers advanced algorithmic methodologies along with their applications and constitutes an excellent resource for students and researchers interested in advanced classes of algorithmic techniques and their applications to pressing realworld problems.
Author(s): Shuchi Chawla
195 Pages
