'1 approximation' diaporamas de présentation

What can we do in sublinear time? 0368.4612 Seminar on Sublinear Time Algorithms Lecture 1

950 views • 88 slides

lidong.wu@utdallas

Small Sensor , Big Data. Ding-Zhu Du University of Texas at Dallas. lidong.wu@utdallas.edu. Small Sensor and Big Data. Lidong Wu University of Texas at Dallas. lidong.wu@utdallas.edu. Digitized World. Drowning in Vast Amount of Data. BigData. Sensor. Outline.

839 views • 70 slides

Approximation algorithms for TSP with neighborhoods in the plane

Approximation algorithms for TSP with neighborhoods in the plane. R90922026 ??? R90922038 ???. The Problem. TSPN: Euclidean TSP with neighborhoods in the plane, i.e., dimention = 2

834 views • 67 slides

On the Hardness Of TSP with Neighborhoods and related Problems

On the Hardness Of TSP with Neighborhoods and related Problems. O. Schwartz & S. Safra. (some slides borrowed from Dana Moshkovitz). Desire: A Tour Around the World. The Problem: Traveling Costs Money. 1795$. But I want to do so much. The Group-TSP (G-TSP). A Minimal cost tour, but

745 views • 63 slides

On the Hardness Of TSP with Neighborhoods and related Problems

On the Hardness Of TSP with Neighborhoods and related Problems. O. Schwartz & S. Safra. (some slides borrowed from Dana Moshkovitz). Desire: A Tour Around the World. The Problem: Traveling Costs Money. 1795$. But I want to do so much. The Group-TSP (G-TSP). A Minimal cost tour, but

636 views • 63 slides

Lecture 21 More Approximation Algorithms

Lecture 21 More Approximation Algorithms. Introduction. Maximum 3DM. 3-Approximation. Any maximal 3DM is a 3-approximation for max 3DM. This is because in the maximum 3DM, every edge (3-set) must have at least one vertex covered by the maximal 3DM. Min Set Cover. Red + Green.

303 views • 30 slides

Lecture 21 More Approximation Algorithms

Lecture 21 More Approximation Algorithms. Introduction. Maximum 3DM. 3-Approximation. Any maximal 3DM is a 3-approximation for max 3DM. This is because in the maximum 3DM, every edge (3-set) must have at least one vertex covered by the maximal 3DM. Min Set Cover. Red + Green.

308 views • 30 slides

Approximation Algorithms for Bandwidth and Storage Allocation

Approximation Algorithms for Bandwidth and Storage Allocation. Reuven Bar-Yehuda Joint work with Michael Beder, Yuval Cohen and Dror Rawitz Technion IIT Slides and paper at: http://www.cs.technion.ac.il/~reuven. The Local-Ratio Technique: Basic definitions .

288 views • 28 slides

A (1+ ?)-Approximation Algorithm for 2-Line-Center

A (1+ ?)-Approximation Algorithm for 2-Line-Center. P.K. Agarwal, C.M. Procopiuc, K.R. Varadarajan Computational Geometry 2003. Outline. Introduction Preliminaries Approximation Algorithm Conclusion. ?. ?. ?. 1.Introduction: Projective clustering.

370 views • 25 slides

Welfare Maximization in Congestion Games

Welfare Maximization in Congestion Games. Liad Blumrosen and Shahar Dobzinski The Hebrew University. Example: File Sharing Systems (Positive Externalities). Example : Scheduling (Negative Externalities). Related Work. Both in game theory and computer science. Examples:

290 views • 20 slides

Approximating Min-Max k-clustering

Approximating Min-Max k-clustering. Asaf Levin The Hebrew University Israel. Problem motivation. We need to partition a set E of clients to k (identical) servers. Each server pays the service cost of the set of clients that is allocated to it.

312 views • 18 slides

Computed Knowledge Base for Quantitative Spectroscopy

Knowledge Engineering and Semantic Web 2012. Computed Knowledge Base for Quantitative Spectroscopy. Alexander Fazliev 1 , Alexey Privezentsev 1 , and Dmitry Tsarkov 2 1 Institute of Atmospheric Optics SB RAS, Zuev Square. 1, 634021 Tomsk, Russia

260 views • 17 slides

Steiner Tree Problem

Euclidean metric. Steiner Point. Cost = 2. 1. 1. Cost = ? 3. Terminals. 1. 1. 1. Rectilinear metric. Cost = 6. Cost = 4. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. Steiner Tree Problem. Given: A set S of points in the plane = terminals

614 views • 8 slides

Assumptions

Assumptions. The pores are large. Their size much exceeds all essential mean free paths (less than 25 nm for YSZ at T>300K) Density of pores (porosity) is small ( p <<1). Thus, the heat flow equation with the position dependent TC coefficient can be used. heat flux. T 2. T 1. L.

205 views • 7 slides