03_GreedyAlgorithms_2.ppt

03_GreedyAlgorithms_2.ppt - Tuesday 13/09/10 Dr. Daniel...

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CSC 30155 Tuesday 13/09/10 Dr. Daniel Hughes daniel.hughes@xjtlu.edu.cn
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This Lecture l Changes to the Group Exercise (10 mins) l Greedy Activity Selection Review (10 mins) l Greedy Algorithms Part 2 (30 mins)
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Supporting Reading for This Week l Optional: l Cormen et al., Introduction to Algorithms , Second Edition. MIT Press, 2001, Chapter 16: Greedy Algorithms (16.1 only). l Kleinberg et al., Algorithm Design , Prentice Hall, 2006, Chapter 4: Greedy Algorithms (4.1 only).
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Timetable Problems l Recall the time-table problem: l Confusion over the time-table occurred due updates in made by the CSSE department that were not implemented by registry. l The correct code for this module is: CS30155: Efficient Sequential Algorithms . l The IMS students have now been transferred to a different module ( CS30785: Semi-structured or Web-Like Databases ), so the course will now return to its original format. l There should be no further disruption, except for some small changes to the group project. l The ICE entry for this course has now been finalized so lecture notes will be online by the end of this week .
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Changes to the Group Exercise l You will now have a little more work to do as your presentation will last 15 minutes per group. l Given the extra time, I expect *every* member of the group to speak. l The tutorial may run a little short this week
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The Friendship Algorithm From ‘Big Bang Theory’, originally aired on CBS A copy of the video clip is available on ICE and also on my teaching page.
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THE PART WE ARE INTERESTED IN
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I only have one team name l Team Name: Inception l Team Members: l Zhang Sheng l Bai Wei l Shen Yulai l Gao Zhen l Qian Binbin l Wang Tian
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Don’t Forget 1. You should send me the other team name ASAP! 2. You need to bring a USB drive with your presentation to our Thursday tutorial session.
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Any Questions?
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CSC 30155 Review of Greedy Activity Selection Dr. Daniel Hughes daniel.hughes@xjtlu.edu.cn
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Greedy Algorithms l In the context of algorithms, a greedy algorithm always makes the locally optimal choice (at each stage). l It does not consider past performance. l It does not consider future performance. l This strategy will succeed where successive greedy ‘local’ choices result in a ‘globally’ optimal result. l This only works if a local decision rule exists that can construct an optimal solution for a problem. l As you might expect there are only a small number of optimal greedy algorithms.
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When are Recursive Greedy Algorithms Optimal? l A simple recursive greedy algorithm produces an optimal answer if the following properties are true: l The Greedy Choice Property : For every instance, there is an optimal solution consistent with the first greedy choice. l
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03_GreedyAlgorithms_2.ppt - Tuesday 13/09/10 Dr. Daniel...

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