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 
Advanced Algorithms by BMS College of Engineering
This PDF deals with some advanced topics in the design of algorithms, focusing on Dynamic Programming. The application domains of DP are discussed and cover classic problems, including Matrix Chain Multiplication, that is, finding an optimal order to multiply many matrices, and Rod Cutting, which is just a typical 4-inch rod problem. Its notes include insights into the steps of DP, its recursive tree structures, and problem-solving through the bottom-up approach. The wide de-balcony of these topics helps the reader understand how DP can be applied to a variety of optimization problems and demonstrates both theoretical and practical aspects of algorithm design.
Author(s): BMS College of Engineering
152 Pages
Advanced Algorithms by Anupam Gupta
These all are very extensive notes on fairly advanced topics in algorithms—both theoretical and practical. Here we deal with discrete algorithms for minimum spanning trees, arborescences (directed spanning trees), dynamic algorithms for problems in graph connectivity, and the shortest path. Other topics discussed in the paper are the combinatorial, algebraic algorithms for graph matching techniques and their corresponding challenges developed within high-dimensional spaces via the technique of dimension reduction and streaming algorithms. Other topics but not triangulated within include the approximate max-flows, online learning, and interior-point methods. The notes thus present a framework in its totality for learning and analyzing super advanced algorithms and thus become a good source to glean insights for an ocean of problems in computer science.
Author(s): Anupam Gupta
309 Pages
Lecture Notes On Design And Analysis Of Algorithms
Lecture Notes on Design and Analysis of Algorithms by Mr. S.K. Sathua, Dr. M.R. Kabat, and Dr. R. Mohanty, published November 14, 2020, is an 80-page document that provides a vital summary of some of the significant notions of algorithms. It first of all provides the basics of the growth of functions and recurrences, while techniques for the solution of these recurrences include substitution and recursion trees. These notes introduce the Master Method for analyzing divide and conquer algorithms and provide worst-case analysis of merge sort, quick sort, and binary search. Other topics it covers are heaps, heap sort, priority queues, and sorting lower bounds, thus proving very valuable for comprehending core principles in algorithm analysis and design.
Author(s): Mr. S.K. Sathua, Dr. M.R. Kabat and Dr. R. Mohanty
80 Pages
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
Data Structures And Algorithms by Sugih Jamin
The book Data Structures and Algorithms by Sugih Jamin covers all the basic concepts of Computer Science in a very balanced way. It involves topics such as linked lists, stacks, and queues to more advanced topics such as binary search trees, heaps, and balanced search trees. Jama's text emphasizes an implementation perspective and algorithmic patterns, which will facilitate a more effective way of understanding and applying the concepts presented. This book will be very useful for the students and professionals who want to establish a sound foundation in data structures and algorithms by providing a solid theoretical background supported by practical examples that explain how problems are solved.
Author(s): Sugih Jamin
NA Pages
The lecture notes on Approximation Algorithms by Shuchi Chawla focus on techniques of designing algorithms that produce near-optimal solutions to complex optimization problems for which finding an exact solution is computationally infeasible. These lecture notes cover general underlying techniques of approximation algorithms, comprising basic building blocks and the foundation needed to deal with problems which are difficult to solve exactly due to computational complexity. These notes by Chawla provide an outline of various methods for approaching different optimization problems and ways of solving them when exact algorithms are not practical. Further, this resource is likely to be extremely helpful with respect to devising and applying approximation algorithms returning good solutions within a reasonable amount of time; hence, this is a must for scholars and practitioners faced with hard optimization problems.
Author(s): Shuchi Chawla
NA Pages
