'Activity selection' presentation slideshows

Lecture 1: The Greedy Method

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T(n) = 4 T(n/3) + ? (n)

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Dynamic Programming

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CS 332: Algorithms

CS 332: Algorithms. NP Completeness. Administrivia. Homework 5 clarifications: Deadline extended to Thursday Dec 7 However, no late assignments will be accepted This is so that I can discuss it in class You may not work with others on this one. Review: Dynamic Programming.

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CS 332: Algorithms

CS 332: Algorithms. Greedy Algorithms Continued. Administrivia. Hand in Homework 4 Hand back remaining midterms. Review: LCS Via Dynamic Programming . Longest common subsequence ( LCS ) problem: Given two sequences x[1..m] and y[1..n], find the longest subsequence which occurs in both

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Greedy Algorithms

Greedy Algorithms. TOPICS Greedy Strategy Activity Selection Minimum Spanning Tree Shortest Paths Huffman Codes Fractional Knapsack. The Greedy Principle. The problem: We are required to find a feasible solution that either maximizes or minimizes a given objective solution .

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UMass Lowell Computer Science 91.404 Analysis of Algorithms Prof. Karen Daniels Fall, 2002

UMass Lowell Computer Science 91.404 Analysis of Algorithms Prof. Karen Daniels Fall, 2002. Monday, 12/2/02 Design Patterns for Optimization Problems Greedy Algorithms. Algorithmic Paradigm Context. Greedy Algorithms. What is a Greedy Algorithm?. Solves an optimization problem

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CPSC 335

CPSC 335. Greedy methods and Backtracking Dr. Marina Gavrilova Computer Science University of Calgary Canada. Dynamic programming. Optimal structure: optimal solution to problem consists of optimal solutions to subproblems Overlapping subproblems : few subproblems in total,

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Algorithm Design approaches

Algorithm Design approaches. Dr. Jey Veerasamy. Petrol cost minimization problem. You need to go from S to T by car, spending the minimum for petrol. S. T. Quick-sort . Merge-sort. Divide & Conquer - characteristics. # of stops minimization problem.

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Greedy Algorithms

Local optimization. Not always yielding a globally optimal solution. Applicable to a wide range of problems (can often come close to the optimal even if it is not guaranteed). Notable greedy algorithms in this course:. Minimum spanning tree algorithms.

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MY SAMM

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