This note describes the following topics: Greedy methods, Dynamic programming, Backtracking, Branch and bound.
Author(s): Annamalai University
96Pages
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
152Pages
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
309Pages
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
125Pages
This note explains the following topics related to Algorithm Analysis and Design: Introduction to Design and analysis of algorithms, Growth of Functions, Recurrences, Solution of Recurrences by substitution,Recursion tree method, Master Method, Design and analysis of Divide and Conquer Algorithms, Worst case analysis of merge sort, quick sort and binary search, Heaps and Heap sort, Priority Queue, Lower Bounds for Sorting.
Author(s): Mr. S.K. Sathua, Dr. M.R. Kabat and Dr. R. Mohanty
80Pages
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
NAPages
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
NAPages
This note covers the following topics: Algorithm Analysis, algorithmic patterns, Standard I/O and iostream, Foundational Data Structures and Basic Abstract Data Types, Linked-list, Stacks and Queues, PA1 walkthrough, Pointer, Hashing, Recursion and Recurrence Relations, Trees, Binary Search Trees, Range and Multidimensional Searches, Heaps, Tries, Balanced Search Trees, Binary-tree Representations of Multi-way Trees.
Author(s): Sugih Jamin
NAPages
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
NAPages
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
195Pages
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
NAPages
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
NAPages
