Advanced Data Structures

Lecture Notes On Design And Analysis Of Algorithms

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

80 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

Introduction to Algorithms by Shayan Oveis Gharan

This book explains the following topics: Stable Matchings, Algrithm Design by Induction, Graphs, Trees or BFS, Connected Comps/Bipartite Graphs, DFS or Topological Ordering, Interval Scheduling, Interval Partitioning, MST, MST, Union find, Closest Points, Master Theorem, Integer Multiplication, Median, Vertex Cover or Set Cover, Network Connectivity, Image Segmentation, Reductions, NP-Completeness, Linear Programming.

Author(s): Shayan Oveis Gharan

NA Pages

Introduction to Algorithms

In computer science, an algorithm is a self-contained step-by-step set of operations to be performed. Topics covered includes: Algorithmic Primitives for Graphs, Greedy Algorithms, Divide and Conquer, Dynamic Programming, Network Flow, NP and Computational Intractability, PSPACE, Approximation Algorithms, Local Search, Randomized Algorithms.

Author(s): Jon Kleinberg and Eva Tardos

459 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

Design and Analysis of Computer Algorithms (PDF 135P)

This lecture note discusses the approaches to designing optimization algorithms, including dynamic programming and greedy algorithms, graph algorithms, minimum spanning trees, shortest paths, and network flows. Also it briefly discusses algorithmic problems arising from geometric settings, that is, computational geometry.

Author(s): David M. Mount

135 Pages

An Introduction to Computational Complexity

This note covers the following topics: Computational Models, Complexity measures, Power increasing resourses, Basic relatton amomg the models and measures, Reducibility, completeness and closure under reductions, Deterministics and nondeterministics logarithmic space, Deterministics polynomial time, Polynomial Hierarchy and Polynomial space.

Author(s): Martin Tompa

85 Pages

Efficient Algorithms for Sorting and Synchronization (Andrew Tridgell, PDF)

This thesis presents efficient algorithms for internal and external parallel sorting and remote data update. Topics covered includes: Internal Parallel Sorting, External Parallel Sorting, The rsync algorithm, rsync enhancements and optimizations and Further applications for rsync.

Author(s): Andrew Tridgell

115 Pages

Dictionary of Algorithms and Data Structures

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

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Algorithms for Programmers (Jrg Arndt) PDF

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

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