Computer Science Bookscomputer algorithm Books

Sorting and Searching Algorithms (Thomas Niemann)

Sorting and Searching Algorithms (Thomas Niemann)

Sorting and Searching Algorithms (Thomas Niemann)

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

Author(s):

s Pages
Similar Books
Lecture Notes on Design and Analysis of Algorithms

Lecture Notes on Design and Analysis of Algorithms

This note describes the following topics: Greedy methods, Dynamic programming, Backtracking, Branch and bound.

s96 Pages
Advanced Algorithms by BMS College of Engineering

Advanced Algorithms by BMS College of Engineering

he PDF covers the following topics related to Computer Algorithms : Dynamic programming, Application domain of DP, Matrix Chain Multiplication, MCP DP Steps, Recursive Tree, Longest Increasing Subsequence, Dynamic programming, Rod cutting -4 inch rod example, DP for rod cutting, Bottom up approach.

s152 Pages
Lecture Notes On Design And Analysis Of Algorithms

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.

s80 Pages
Fundamentals of Algorithms with Applications

Fundamentals of Algorithms with Applications

This note explains the following topics: Growth of functions, Basic data structures, Sorting and Selection, Fundamental techniques, Dynamic programming and Graphs, Graph algorithms, NP-Completeness and approximation algorithms, Randomized Algorithms.

sNA Pages
Advanced Algorithms Lectures by Shuchi Chawla

Advanced Algorithms Lectures by Shuchi Chawla

This note introduces students to advanced techniques for the design and analysis of algorithms, and explores a variety of applications. Topics covered includes: Greedy algorithms, Dynamic programming, Network flow applications, matchings, Randomized algorithms, Karger's min-cut algorithm, NP-completeness, Linear programming, LP duality, Primal-dual algorithms, Semi-definite Programming, MB model contd., PAC model, Boosting in the PAC framework.

s195 Pages
Introduction to Algorithms Lecture Notes

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.

sNA Pages