Fundamentals of Algorithms with Applications
Michael T. Goodrich's Fundamentals of Algorithms with Applications gives good coverage to algorithmic principles and their application. It covers growth functions, basic data structures, sorting, selection, dynamic programming, graph algorithms-the principles of algorithm design. Advanced topics such as NP-completeness, approximation algorithms, and randomized algorithms are also explored. Goodrich's book is well-recognized for its lucid explanations of the exercises on these complex topics to make them understandable and lively. Theoretically sound, with practical applications, this book suits both students and professionals in developing problem-solving skills and computational understanding.
Author(s): Michael T. Goodrich
NA Pages 
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
Advanced Algorithms by Anupam Gupta
The PDF covers the following topics related to Computer Algorithms, Discrete Algorithms, Minimum Spanning Trees, Arborescences, Directed Spanning Trees, Dynamic Algorithms for Graph Connectivity, Shortest Paths in Graphs, LowStretch Spanning Trees, Graph Matchings I, Combinatorial Algorithms, Graph Matchings II, Weighted Matchings, Graph Matchings III, Algebraic Algorithms, The Curse of Dimensionality, and Dimension Reduction, Dimension Reduction and the JL Lemma, Streaming Algorithms, Dimension Reduction, Singular Value Decompositions, From Discrete to Continuous Algorithms, Online Learning, Experts and Bandits, Solving Linear Programs using Experts, Approximate MaxFlows using Experts, The Gradient Descent Framework, Mirror Descent, The Centroid and Ellipsoid Algorithms, InteriorPoint Methods, Combating Intractability, Approximation Algorithms via SDPs, Online Algorithms, Additional Topics, Prophets and Secretaries.
Author(s): Anupam Gupta
309 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
Lecture Notes On Design And Analysis Of Algorithms
This note explains the following topics related to Algorithm Analysis and Design, Introduction to Design and analysis of algorithms, Growth of Functions, Recurrences, Solution of Recurrences by substitution,Recursion tree method, Master Method, Design and analysis of Divide and Conquer Algorithms, Worst case analysis of merge sort, quick sort and binary search, Heaps and Heap sort, Priority Queue, Lower Bounds for Sorting.
Author(s): Mr. S.K. Sathua, Dr. M.R. Kabat and Dr. R. Mohanty
80 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
