'Euclidean space' diaporamas de présentation

IPAM-UCLA Tutorial May 14-18, 2001 GBM in Image Processing, Computer Vision, and Computer Graphics

IPAM-UCLA Tutorial May 14-18, 2001 GBM in Image Processing, Computer Vision, and Computer Graphics. Guillermo Sapiro Electrical and Computer Engineering University of Minnesota guille@ece.umn.edu. Supported by IPAM, NSF, ONR. GBM: Moving Curves. Basic curve evolution. Planar curve:

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An introduction to Causal sets

960 views • 76 slides

Reading Knot Diagrams

Reading Knot Diagrams. A Computer Vision Project By Dale Clements Advisors: Victor Milenkovic & Kenneth Baker. Knot Theory. Dr. Baker Mathematical Knots a knot is an embedding of a circle in 3-dimensional Euclidean space Closed Represented by a Knot Diagram. Knot Diagrams.

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Spectral Surface Quadrangulation

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6.853: Topics in Algorithmic Game Theory

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QUARKS, GLUONS AND NUCLEAR FORCES

QUARKS, GLUONS AND NUCLEAR FORCES. Paulo Bedaque University of Maryland, College Park. strong nuclear force: binds neutrons and protons into nuclei. Quantum Chromodynamics (QCD). What do we know ?. 1) NN phase shifts. 1 S 0 neutron-proton. What do we know ?.

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CS361

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Comparison of Precoding Schemes for Digital Subscriber Lines

Comparison of Precoding Schemes for Digital Subscriber Lines. Project presentation for ECE 492 Vishnu Prasan April 19, 2007. Agenda. Introduction Precoding in uncoded Transmissions for THP and FLP Precoding with coded modulation for THP and FLP

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Taming Dynamic and Selfish Peers

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Presented by Nagesh Adluru

KERNEL INDEPENDENT COMPONENT ANALYSIS BY FRANCIS BACH & MICHAEL JORDAN International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2003. Presented by Nagesh Adluru. Goal of the Paper.

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Detecting Phantom Nodes in Wireless Sensor Networks

Detecting Phantom Nodes in Wireless Sensor Networks. Joengmin Hwang, Tian He, Yongdae Kim (ACM Infocom2007) Presenter : Justin. Main ideas. Two factors: Prevent the phantom nodes from generating consistent ranging (distance) claims to multiple honest nodes.

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Special embeddings into Euclidean space Svetlana I. Bogataya Higher school of economics National research university; Mo

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Motion Planning Geometrical Formulation of the Piano Mover Problem

Motion Planning Geometrical Formulation of the Piano Mover Problem. Configuration Space. Environment made of bodies: compact and connected domains of the Euclidean space . Body placement : translation-rotation composition Placement Space P. Obstacles : finite number of fixed bodies

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Geometry of Shape Manifolds

Geometry of Shape Manifolds. Constraints define a manifold embedded in q 0 + L 2 Move along manifold by moving in tangent space and projecting back to manifold Tangent space is infinite dimensional, but normal space is characterized by three constraints defined in f 1. Tangents and Normals.

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Chapter 9

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Informational Complexity Notion of Reduction for Concept Classes

Informational Complexity Notion of Reduction for Concept Classes. Shai Ben-David Cornell University, and Technion Joint work with Ami Litman Technion. Measures of the Informational Complexity of a class. The VC-dimension of the class.

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MA4266 Topology

Lecture 9. . MA4266 Topology. Wayne Lawton Department of Mathematics S17-08-17, 65162749 matwml@nus.edu.sg http://www.math.nus.edu.sg/~matwml/ http://arxiv.org/find/math/1/au:+Lawton_W/0/1/0/all/0/1. Path Connected Spaces.

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Ultra-low-dimensional embeddings of doubling metrics

Ultra-low-dimensional embeddings of doubling metrics. T-H. Hubert Chan Max Planck Institute, Saarbrucken Anupam Gupta Carnegie Mellon University Kunal Talwar Microsoft Research SVC. Doubling Dimension. Def: Every ball of radius 2R can be covered by 2 k balls of radius R

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582 views • 7 slides

UCF REU Week 7

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