Introduction to Algorithms Lecture Notes

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, Prim's Algorithm, Fourier transforms and Rabin-Karp Algorithm.

Author(s): Dr. Subasish Mohapatra

125 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

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

Analysis and Design of Computer Algorithms by Ganesh Kumar

This note covers the following topics: Divide And Conquer Strategy, Greedy Method, Minimum Spanning Trees, Dynamic Programming, Optimal Binary search trees, Backtracking Method, Branch and Bound, Lower bound Theory.

Author(s): Sh. Ganesh Kumar

85 Pages

Data Structures and Algorithm Analysis

This book is designed as a teaching text that covers most standard data structures, but not all. A few data structures that are not widely adopted are included to illustrate important principles.

Author(s): Clifford A. Shaffer

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

Lecture Notes for Algorithm Analysis and Design (PDF 124P)

This note covers the following topics related to Algorithm Analysis and Design: Model and Analysis, Warm up problems, Brute force and Greedy strategy, Dynamic Programming, Searching, Multidimensional Searching and Geometric algorithms, Fast Fourier Transform and Applictions, String matching and finger printing, Graph Algorithms, NP Completeness and Approximation Algorithms.

Author(s): Sandeep Sen

128 Pages

Information Theory, Inference, and Learning Algorithms (David J.C. MacKay)

Currently this section contains no detailed description for the page, will update this page soon.

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Sorting and Searching Algorithms (Thomas Niemann)

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Handbook of Algorithms and Data Structures (G. Gonnet, R. Baeza Yates)

Currently this section contains no detailed description for the page, will update this page soon.

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