'Greedy choice property' presentation slideshows

Chapter 5

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??? Greedy Algorithm

??? Greedy Algorithm. ?????? ??????. 5.1 Elements of Greedy Algorithms 5.2 An activity-selection problem 5.3 Huffman codes 5.4 Minimal spanning tree problem. ??. Greedy ??????? Greedy ??? ????? ?????????? Greedy ?????????. 5.1 Elements of Greedy Algorithms. Optimal.

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Analysis of Algorithms CS 477/677

Analysis of Algorithms CS 477/677. Instructor: Monica Nicolescu Lecture 18. Interval Partitioning. Lecture j starts at s j and finishes at f j Goal: find minimum number of classrooms to schedule all lectures so that no two occur at the same time in the same room

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Analysis of Algorithms CS 477/677

Analysis of Algorithms CS 477/677. Instructor: Monica Nicolescu Lecture 17. Greedy Algorithms. Similar to dynamic programming, but simpler approach Also used for optimization problems Idea: When we have a choice to make, make the one that looks best right now

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Design and Analysis of Algorithms Approximation algorithms for NP-complete problems

Design and Analysis of Algorithms Approximation algorithms for NP-complete problems. Haidong Xue Summer 2012, at GSU. Approximation algorithms for NPC problems. If a problem is NP-complete, there is very likely no polynomial-time algorithm to find an optimal solution

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Design and Analysis of Algorithms Activity selection, 0-1 knapsack, and fractional knapsack

Design and Analysis of Algorithms Activity selection, 0-1 knapsack, and fractional knapsack. Haidong Xue Summer 2012, at GSU. Activity selection. Activity = <start time s, finish time f>, f>=s A set of activities:. a1. a2. a3. 12. 11. 10. 9. 15. 7. 5. 3. 4. 6. 2. 1. 0. 16.

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Greedy Algorithms and Matroids

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CS 332: Algorithms

CS 332: Algorithms. Dynamic Programming Greedy Algorithms. Administrivia. Hand back midterm Go over problem values. Review: Amortized Analysis. To illustrate amortized analysis we examined dynamic tables 1. Init table size m = 1 2. Insert elements until number n > m

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Design and Analysis of Algorithms Minimum Spanning trees

Design and Analysis of Algorithms Minimum Spanning trees. Haidong Xue Summer 2012, at GSU. What are trees in undirected graphs?. We are familiar with a rooted directed tree, such as: Binary search tree Heap They look like: You know which one the root is Who the parent is

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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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Design Methods for Algorithms

Design Methods for Algorithms. Andreas Klappenecker. Design Methods. We have discussed examples of the following algorithm design principles: Dynamic Programming Paradigm Greedy Paradigm Divide-and-Conquer Paradigm. Main Question.

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Summary: Design Methods for Algorithms

Summary: Design Methods for Algorithms. Andreas Klappenecker. Design Methods. We have discussed examples of the following algorithm design principles: Dynamic Programming Paradigm Greedy Paradigm Divide-and-Conquer Paradigm. Main Question.

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Lecture 6

Lecture 6. Greedy Algorithm. Topics. Reference: Introduction to Algorithm by Cormen Chapter 17: Greedy Algorithm. Greedy Algorithm. Algorithm for optimization problems typically go through a sequence of steps, with a set of choices at each step.

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