Purely Functional 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 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

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

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

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

Data Structures and Algorithms The Basic Toolbox

This book is a concise introduction to this basic toolbox, intended for students and professionals familiar with programming and basic mathematical language.

Author(s): K. Mehlhorn and P. Sanders

NA Pages

Information Theory, Inference, and Learning Algorithms (David J.C. MacKay)

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

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Pages

Information Retrieval (C.J. van Rijsgergen)

The material of this book is aimed at advanced undergraduate information (or computer) science students, postgraduate library science students, and research workers in the field of IR. Some of the chapters, particular chapter 6, make simple use of a little advanced mathematics.

Author(s): C.J. van Rijsgergen

NA Pages

Algorithms for Programmers (Jrg Arndt)

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

Author(s):

Pages