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 
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 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
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
Advanced Algorithms by Prof. Michel Goemans
Advanced Algorithms" by Prof. Michel Goemans is an advanced-level text focused on sophisticated algorithmic methods for doctoral students and researchers. Advanced subjects like Fibonacci heaps, network flows, and dynamic trees are explained in detail, together with linear programming-the Goldberg-Tarjan min-cost circulation algorithm, approximation algorithms, max-cut problems, and conic programming. Goemans explains such advanced concepts in great detail, merging theory and practice. This text will be useful for anyone interested in deeply understanding modern algorithms and how they may be implemented and includes a conceptual framework for rigorous solutions to complex computational problems.
Author(s): Prof. Michel Goemans
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
