'Spanner' presentation slideshows

An optimal dynamic spanner for points residing in doubling metric spaces

An optimal dynamic spanner for points residing in doubling metric spaces. Lee-Ad Gottlieb NYU Weizmann. Liam Roditty Weizmann. Spanners. A spanner for graph G is a subgraph H H contains all vertices in G H contains only some edges of G. G. H. 1. 2. 2. 1. 1. 1. 1. Spanners.

701 views • 56 slides

An optimal dynamic spanner for points residing in doubling metric spaces

An optimal dynamic spanner for points residing in doubling metric spaces. Lee-Ad Gottlieb NYU Weizmann. Liam Roditty Weizmann. Spanners. A spanner for graph G is a subgraph H H contains all vertices in G H contains only some edges of G. G. H. 1. 2. 2. 1. 1. 1. 1. Spanners.

566 views • 56 slides

Additive Spanners for k -Chordal Graphs

Additive Spanners for k -Chordal Graphs. V. D. Chepoi, F.F. Dragan , C. Yan. University Aix-Marseille II, France Kent State University, Ohio, USA. Sparse t -Spanner Problem. Given unweighted undirected graph G=(V,E) and integers t, m.

515 views • 40 slides

Network Flow Spanners

427 views • 31 slides

Jie Gao, Leonidas Guibas, An Nguyen Computer Science Department Stanford University

Flexible Spanners: A Proximity and Collision Detection Tool for Molecules and Other Deformable Objects. Jie Gao, Leonidas Guibas, An Nguyen Computer Science Department Stanford University. Most forces in nature are short range: e.g.,neighbor lists in MD. Self-collision detection.

402 views • 25 slides

Network Flow Spanners

312 views • 23 slides

A Simple and Efficient Kinetic Spanner

A Simple and Efficient Kinetic Spanner. M.A. Abam MADALGO. J. Gudmundsson NICTA. M. de Berg TU Eindhoven. dilation. Geometric spanners. geometric network:. vertices: set of points in R d edge length: Euclidean length. (13,7). (3,7). 10. q. p. length ? t ? | pq |.

390 views • 22 slides

Steiner Transitive-Closure Spanners of Low-Dimensional Posets

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A PREPROCESSING METHOD AND ROTATION INVARIANT 2D OBJECT RECOGNITION USING BPG NEURAL NETWORKS

A PREPROCESSING METHOD AND ROTATION INVARIANT 2D OBJECT RECOGNITION USING BPG NEURAL NETWORKS. Irina Topalova . Preprocessing. Backpropagation NN. Class. Image. Introduction to NN processing. Quality. Complex Simple. Simple Complex. Accuracy. The Problem.

304 views • 16 slides

The Safe Working Practice of Changing Out a Raisebore Reaming Head Underground

335 views • 16 slides

Algorithms for Radio Networks Exercise 6

232 views • 14 slides

Formwork Accessories

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105 views • 10 slides

Wireless Sensor Networks 20th Lecture 17.01.2007

198 views • 9 slides