PPT-1 Spanning Trees, greedy algorithms

Lecture 22 CS2110 Fall 2017 1 We demo A8 Your space ship is on earth and you hear a distress signal from a distance Planet X Your job Rescue stage Fly your ship to Planet X as fast as you can. - S. Kapoor and H. Ramesh. Speakers: . 李孟韓. 1. , . 林蔚茵. 2. , . 莊秋芸. 3. , . 黃稚穎. 4. Reference. H. N. Gabow and E. W. Myers: Finding all spanning trees of directed and undirected graphs, . . Spanning Trees. CSE 680. Prof. Roger Crawfis. Tree. We call an undirected graph a . tree . if the graph is . connected . and. . contains . no cycles. .. Trees:. Not Trees:. Not connected. Has a . Spanning Tree Protocol Enhancements. 802.1D-1998: The legacy standard for bridging and STP.. CST: Assumes one spanning-tree instance for the entire bridged network, regardless of the number of VLANs. . to . Greedy Routing Algorithms . in Ad-Hoc Networks. ○. Truong . Minh . Tien. Joint work with. Jinhee. . Chun, . Akiyoshi. . Shioura. , . and Takeshi . Tokuyama. Tohoku University. Japan. Our . Problem. Hamed Pirsiavash, Deva . Ramanan. , . Charless. . Fowlkes. Department of Computer Science, UC Irvine. 2. Estimate number of tracks and their extent. Do not initialize manually. Estimate birth and death of each track. Akhil. Langer. , . Ramprasad. . Venkataraman. , . Laxmikant. Kale. Parallel Programming Laboratory. Overview. Introduction. Problem Statement. Distributed Algorithms. Shrink-and-balance. Shrink-and-hash. Trees. Spring 2014. Sukumar Ghosh. What is a tree?. Rooted tree: recursive definition. Rooted tree terminology. Rooted tree terminology. A . subtree. Rooted tree terminology. Important properties of trees. 1. Uri Zwick. Tel Aviv University. October 2015. Last updated. : November 18, . 2015. Spanning Trees. 2. A . tree. is a . connected. . acyclic . graph (contains no . cycles. ). .. A . spanning tree . The two key components. Optimal Sub-structure. You solve the problem by solving a sub-problem optimally. Greedy Property. Using the choice that seems best at the moment leads to the optimal result. This is tougher to show!. - Week 13. 2. Problem: Laying Telephone Wire. Central office. 3. Wiring: Naive Approach. Central office. Expensive!. 4. Wiring: Better Approach. Central office. Minimize the total length of wire connecting . Jingtao Zhu. May 13rd,2016. “Efficient Influence Maximization . in Social Networks. ”. . Written by Chen Wei, Yajun Wang, and Siyu Yang. . Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. . Greedy . Algorithms. CSE 680. Prof. Roger Crawfis. Optimization . Problems. For most optimization problems you . want to find, not just . a. solution, but the . best. . solution.. A . greedy algorithm . Introduction to Algorithms Greedy Algorithms CSE 680 Prof. Roger Crawfis Optimization Problems For most optimization problems you want to find, not just a solution, but the best solution. A Fall 20151 Week . 7. CSCI-141. Scott C. Johnson. Say we go to the bank to cash our paycheck. We ask the teller for the fewest bills and coins as possible. Moments later the teller gives us our money and we leave.