PPT-Improved Approximation Algorithms for the Spanning Star For

Prasad Raghavendra Ning Chen C Thach Nguyen Atri Rudra Gyanit Singh University of Washington Roee Engelberg Technion University. Sparsifying. Rajmohan Rajaraman. Northeastern University, Boston. May 2012. Chennai Network Optimization Workshop. Spanning and Sparsifying. 1. Sparse Approximations of Graphs. How well can an undirected graph G = (V,E) be approximated by a sparse graph H?. 1. Tsvi. . Kopelowitz. Knapsack. Given: a set S of n objects with weights and values, and a weight bound:. w. 1. , w. 2. , …, w. n. , B (weights, weight bound).. v. 1. , v. 2. , …, v. n. (values - profit).. Sometimes we can handle NP problems with polynomial time algorithms which are guaranteed to return a solution within some specific bound of the optimal solution. within a constant . c. . of the optimal. Akhil. Langer. , . Ramprasad. . Venkataraman. , . Laxmikant. Kale. Parallel Programming Laboratory. Overview. Introduction. Problem Statement. Distributed Algorithms. Shrink-and-balance. Shrink-and-hash. Algorithms. and Networks 2015/2016. Hans L. . Bodlaender. Johan M. M. van Rooij. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. A. A. A. A. A. A. A. What to do if a problem is. Node and Edge Searching . Spanning Tree . Problems. Sheng-Lung Peng. Department of Computer Science and Information Engineering. National Dong . Hwa. University, . Hualien. 974, Taiwan. Outline. Introduction. Problem. Yan Lu. 2011-04-26. Klaus Jansen SODA 2009. CPSC669 Term Project—Paper Reading. 1. Problem Definition. 2. Approximation Scheme. 2.1 Instances with similar capacities. 2.2 General cases . Outline. Julia Chuzhoy. Toyota Technological Institute at Chicago. Routing Problems. Input. : Graph G, source-sink pairs (s. 1. ,t. 1. ),…,(. s. k. ,t. k. ).. Goal. : Route as many pairs as possible; minimize edge congestion.. Grigory. . Yaroslavtsev. . Penn State + AT&T Labs - Research (intern). Joint work with . Berman (PSU). , . Bhattacharyya (MIT). , . Makarychev. (IBM). , . Raskhodnikova. (PSU). Directed. Spanner Problem. and . Some Applications. Chandra . Chekuri. Univ. of Illinois, Urbana-Champaign. Based on joint work. Near-linear-time . approximation schemes for some implicit fractional packing problems.  . with . Stochastic . Optimization. Anupam Gupta. Carnegie Mellon University. IPCO Summer . School. Approximation . Algorithms for. Multi-Stage Stochastic Optimization. {vertex cover, . S. teiner tree, MSTs}. When the best just isn’t possible. Jeff Chastine. Approximation Algorithms. Some NP-Complete problems are too important to ignore. Approaches:. If input small, run it anyway. Consider special cases that may run in polynomial time. . 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 . MST . and . metric-TSP Interdiction. Chaitanya Swamy. University of Waterloo. Joint work with . André . Linhares. University of Waterloo. Minimum spanning tree (MST) interdiction. Given: graph . G. =(V,.