PPT-Algorithms Lecture 25 Minimum cut

Minimum cut Recall that a cut in a graph is a partition of its vertices into two nonempty subsets A B The size of a cut is the number of edges from vertices in A to vertices in B Ie the number of edges . Rahul. . Santhanam. University of Edinburgh. Plan of the Talk. Preliminaries and Motivation. Informational Bottlenecks: Proof Complexity and Related Models. Computational Bottlenecks: OPP and Compression. Annie . Yang and Martin Burtscher*. Department of Computer Science. Highlights. MPC compression algorithm. Brand-new . lossless . compression algorithm for single- and double-precision floating-point data. April 22, 2010. Last Time. GMM Model Adaptation. MAP (Maximum A Posteriori). MLLR (Maximum Likelihood Linear Regression). UMB-. MAP. for speaker recognition. Today. Graph Based Clustering. Minimum Cut. Amrinder Arora. Permalink: http://standardwisdom.com/softwarejournal/presentations/. Summary. Online algorithms show up in . many. practical problems.. Even if you are considering an offline problem, consider what would be the online version of that problem.. CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS OUT CUT THIS Introduction. Minimum-Mean Cycle Canceling . Algorithm. Repeated Capacity Scaling . Algorithm. Enhanced Capacity Scaling. Algorithm. Summary. Minimum Cost Flow Problem –. Strongly Polynomial Algorithms. Instructor: Arun Sen. Office: BYENG . 530. Tel: 480-965-6153. E-mail: asen@asu.edu. Office Hours: . MW 3:30-4:30 or by appointment. TA: . TBA. Office. : TBA. Tel: . TBA. E-mail: . TBA. Office Hours. : . Problem - a well defined task.. Sort a list of numbers.. Find a particular item in a list.. Find a winning chess move.. Algorithms. A series of precise steps, known to stop eventually, that solve a problem.. Richard Anderson. Winter 2013. Lecture 4. Announcements. Reading. For today, sections 4.5, 4.7, . 4.8, 5.1, 5.2. Interval Scheduling. Highlights from last lecture. Greedy Algorithms. Dijkstra’s. Algorithm. Let's first look at the . tests for 1 search. :. N. lg. 2. N. 8. 3. 16. 4. 1M. 20. 1G. 30. …. …. 64. 6. 32. 5. 1024. 10. 3. Lecture 9: Algorithm Analysis. Now consider multiple searches. Let's say for example I need to do 1 million searches of 1 million items. Lecture 18. May 29, . 2014. May 29, 2014. 1. CS38 Lecture 18. May 29, 2014. CS38 Lecture 18. 2. Outline. coping with . intractibility. approximation algorithms. set cover. TSP. center selection. randomness in algorithms. M. Pawan Kumar. http://. www.robots.ox.ac.uk. /~oval/. Slides available online http://. mpawankumar.info. Energy Minimization. V. a. V. b. V. c. V. d. Energy Minimization. V. a. V. b. V. c. V. d. 2. 5. NESA . PD. – Implementing the HSC Minimum Standard. How can students demonstrate the HSC minimum standard?. Students can demonstrate the HSC minimum standard by passing the HSC minimum standard online tests. cutty. ”. This means taking out unnecessary pauses between actors’ delivery of dialogue lines. Sometimes it . means . tightening the gaps within dialogue sentences through the use of carefully placed cutaways. It may also mean losing redundant lines of dialogue, after the director has reviewed your cut..