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.
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.
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.
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.
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
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.
note covers the following topics: Encryption Algorithms, Genetic
Algorithms, Geographic Information Systems Algorithms, Sorting
Algorithms, Search Algorithms, Tree Algorithms, Computational
Geometry Algorithms, Phonetic Algorithms and Project Management