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, Low-Stretch 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 Max-Flows using Experts, The Gradient Descent Framework, Mirror Descent, The Centroid and Ellipsoid Algorithms, Interior-Point Methods, Combating Intractability, Approximation Algorithms via SDPs, Online Algorithms, Additional Topics, Prophets and Secretaries.
Author(s): Anupam Gupta
309 Pages 
Lecture Notes On Design And Analysis Of Algorithms
This note covers the following topics: Design and analysis of algorithms, Growth of Functions, Recurrences, Solution of Recurrences by substitution, Recursion tree method, Master Method, Worst case analysis of merge sort, quick sort and binary search, Design and analysis of Divide and Conquer Algorithms, Heaps and Heap sort, Priority Queue, Lower Bounds for Sorting, Dynamic Programming algorithms, Matrix Chain Multiplication, Elements of Dynamic Programming, Longest Common Subsequence, Greedy Algorithms, Activity Selection Problem, Elements of Greedy Strategy, Fractional Knapsack Problem, Huffman Codes, Graph Algorithm - BFS and DFS, Minimum Spanning Trees, Kruskal algorithm, Prim's Algorithm, Fourier transforms and Rabin-Karp Algorithm.
Author(s): Dr. Subasish Mohapatra
125 Pages
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.
Author(s): Michael T. Goodrich
NA Pages
Advanced Algorithms by Prof. Michel Goemans
This note is designed for doctoral students interested in theoretical computer science. Topics covered includes: Fibonacci heaps, Network flows, Maximum flow, minimum cost circulation, Goldberg-Tarjan min-cost circulation algorithm, Cancel-and-tighten algorithm; binary search trees, Splay trees, Dynamic trees , Linear programming, LP: duality, geometry, simplex, LP: complexity, ellipsoid algorithm, LP: applications of the ellipsoid algorithm, Conic programming, Approximation algorithms, Max-cut and sparsest-cut, Multi-commodity flows and metric embeddings, Convex hulls.
Author(s): Prof. Michel Goemans
NA Pages
Distributed Algorithms Lecture Notes
Distributed algorithms are algorithms designed to run on multiple processors, without tight centralized control. Topics covered includes: Variations in model assumptions, Top-level organization is by the timing model, Synchronous model, Asynchronous model, Partially synchronous model, Synchronous networks.
Author(s): Prof. Nancy Lynch
NA Pages
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.
Author(s): Shuchi Chawla
195 Pages
The field of approximation algorithms has developed in response to the difficulty in solving a good many optimization problems exactly. This note will present general techniques that underly these algorithms.
Author(s): Shuchi Chawla
NA Pages
