Advanced Algorithms Lectures and Resources

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

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

Advanced Algorithms Lectures and Resources

This note will cover classic and modern algorithmic ideas that are central to many areas of Computer Science. The focus is on most powerful paradigms and techniques of how to design algorithms, and measure their efficiency. The topics will include hashing, sketching, dimension reduction, linear programming, spectral graph theory, gradient descent, multiplicative weights, compressed sensing, and others.

Author(s): Alex Andon

NA Pages

Design and Analysis of Algorithms

This is an intermediate algorithms course note with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography.

Author(s): Prof. Erik Demaine, Prof. Srinivas Devadas and Prof. Nancy Lynch

NA Pages

Design and Analysis of Algorithms Course Notes

This note explains core material in data structures and algorithm design, and also helps students prepare for research in the field of algorithms. Topics covered includes: Splay Trees, Amortized Time for Splay Trees, Maintaining Disjoint Sets, Binomial heaps, F-heap, Minimum Spanning Trees, Fredman-Tarjan MST Algorithm, Light Approximate Shortest Path Trees, Matchings, Hopcroft-Karp Matching Algorithm, Two Processor Scheduling, Network Flow - Maximum Flow Problem, The Max Flow Problem and Max-Flow Algorithm.

Author(s): Samir Khuller

161 Pages

Design And Analysis Of Algorithms by Herbert Edelsbrunner

This book focuses on fundamental data structures and graph algorithms. The emphasis will be on algorithm design and on algorithm analysis.

Author(s): Herbert Edelsbrunner

95 Pages

Algorithms and Data Structures Lecture Materials

This note will examine various data structures for storing and accessing information together with relationships between the items being stored, and algorithms for efficiently finding solutions to various problems, both relative to the data structures and queries and operations based on the relationships between the items stored. Topics covered includes: Algorithm analysis, List, stacks and queues, Trees and hierarchical orders, Ordered trees, Search trees, Priority queues, Sorting algorithms, Hash functions and hash tables, Equivalence relations and disjoint sets, Graph algorithms, Algorithm design and Theory of computation.

Author(s): Douglas Wilhelm Harder

NA Pages

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

Data Structures and Algorithm Analysis

This book is designed as a teaching text that covers most standard data structures, but not all. A few data structures that are not widely adopted are included to illustrate important principles.

Author(s): Clifford A. Shaffer

NA Pages

Algorithms for Programmers (Jrg Arndt) PDF

Currently this section contains no detailed description for the page, will update this page soon.

Author(s):

Pages