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 
This book contains below topics, Recursion, Backtracking, Dynamic Programming, Greedy Algorithms, Basic Graph Algorithms, Depth First Search, Minimum Spanning Trees, Shortest Paths, All Pairs Shortest Paths, Maximum Flows and Minimum Cuts, Applications of Flows and Cuts, NP Hardness.
Author(s): Jeff Erickson, University of Illinois Urbana-Champaign
472 Pages
Lecture Notes on Design and Analysis of Algorithms
This note describes the following topics, Greedy methods, Dynamic programming, Backtracking, Branch and bound.
Author(s): Annamalai University
96 Pages
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.
Author(s): BMS College of Engineering
152 Pages
Advanced Algorithms by Anupam Gupta
The PDF covers the following topics related to Computer Algorithms, Discrete Algorithms, Minimum Spanning Trees, Arborescences, Directed Spanning Trees, Dynamic Algorithms for Graph Connectivity, Shortest Paths in Graphs, LowStretch Spanning Trees, Graph Matchings I, Combinatorial Algorithms, Graph Matchings II, Weighted Matchings, Graph Matchings III, Algebraic Algorithms, The Curse of Dimensionality, and Dimension Reduction, Dimension Reduction and the JL Lemma, Streaming Algorithms, Dimension Reduction, Singular Value Decompositions, From Discrete to Continuous Algorithms, Online Learning, Experts and Bandits, Solving Linear Programs using Experts, Approximate MaxFlows using Experts, The Gradient Descent Framework, Mirror Descent, The Centroid and Ellipsoid Algorithms, InteriorPoint Methods, Combating Intractability, Approximation Algorithms via SDPs, Online Algorithms, Additional Topics, Prophets and Secretaries.
Author(s): Anupam Gupta
309 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 Kargers mincut algorithm, NPcompleteness, together with linear programming, primaldual algorithms, and semidefinite 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 realworld problems.
Author(s): Shuchi Chawla
195 Pages
The lecture notes on Approximation Algorithms by Shuchi Chawla focus on techniques of designing algorithms that produce nearoptimal 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
