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 
Lecture Notes on Design and Analysis of Algorithms
These ecture notes give a comprehensive introduction to the basic techniques in the design and analysis of algorithms. It covers major methodologies, including greedy methods, which build up solutions piece by piece; dynamic programming (DP), which breaks down problems into simpler subproblems, solves them, and memorizes their solutions; and backtracking, which incrementally generates candidates for solutions and discards those that cannot satisfy criteria. It also discusses the method of Branch and Bound, where all branches on a solution space are systematically explored until the best possible solution is obtained. These methods are crucial in the design of nice algorithms with a view to efficiency, and they form the basis of complex computational problems that require solutions.
Author(s): Annamalai University
96 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
Design And Analysis Of Algorithms by Herbert Edelsbrunner
Design and Analysis of Algorithms is a book by Herbert Edelsbrunner that gives a detailed description of the basic principles and techniques of algorithms. The book offers basic data structures and some graph algorithms, making it one of the best platforms to understand how to design and analyze algorithms. It emphasizes the developers developing a good and efficient algorithm, followed by the analysis of complexity. It contains basic data structures such as trees, graphs, and several strategies of algorithmic problem-solving. Edelsbrunner's approach in the text marries theoretical insights with the practical details that are absolutely necessary to implement his algorithms. So, his book will be of great use to students, researchers, and practitioners concerned with algorithms in computer science. The book will help the readers to incite strong skills in algorithmic techniques and their applications and create an overview necessary for a deeper understanding of computational efficiency and problem solving.
Author(s): Herbert Edelsbrunner
95 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
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 Karger's min-cut algorithm, NP-completeness, together with linear programming, primal-dual algorithms, and semi-definite 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 real-world problems.
Author(s): Shuchi Chawla
195 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
