Manifold learning: MDS and Isomap

Apr 26, 2013

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Review. ClusteringClassificationSemi-supervised learningFeature reductionKernel methods. Manifold learning. Outline of lecture. IntuitionLinear method- PCALinear method- MDSNonlinear method- IsomapSummary. Why Dimensionality Reduction. The curse of dimensionalityNumber of potential features can be hugeImage data: each pixel of an imageA 64X64 image = 4096 featuresGenomic data: expression levels of the genesSeveral thousand featuresText categorization: frequencies of phrases in9443

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Manifold learning: MDS and Isomap

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Modern Automotive Technology

Modern Automotive Technology by Russell Krick Publisher The Goodheart-Willcox Co., Inc. Tinley Park, Illinois PowerPoint for Chapter 13 Engine Top End Construction Contents Cylinder head construction Valve train construction Intake manifold construction Exhaust manifold construction

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4.2.11

4.2.11. Installing Manifold Cylinders or Tanks. When installing manifold DOT cylinders or ASME tanks, it is essential to understand and identify the different components and applications required by safety codes for their installation. . In this module you will learn to:

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HYDRAULICS_5

HYDRAULICS_5. Design of Irrigation Systems by László Ormos. DESIGN OF MANIFOLD. The manifold is a pipe with multiple outlets to the inlets of lateral pipes. The size of plot, the flow rate and the number of shifts in a complete irrigation cycle should be taken into consideration.

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Modeling and Parallel Simulation of Multicore Systems with Manifold

Modeling and Parallel Simulation of Multicore Systems with Manifold. Introduction. Manifold Execution Model and System Architecture. Execution model Software architecture Simulation kernel Manifold component Building system models. Execution Model: high-level overview.

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LH2 Manifold R & D

LH2 Manifold R & D. The driving physics issue in Mucool LH2 R & D is now fluid flow and heat removal Two separate absorber designs What is “certification”? What are the fundamental limits of operation? Flow simulations What are the first direct measurements?

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Richard G. Baraniuk Chinmay Hegde

Manifold Learning in the Wild A New Manifold Modeling and Learning Framework for Image Ensembles Aswin C. Sankaranarayanan Rice University. Richard G. Baraniuk Chinmay Hegde. Sensor Data Deluge. Internet Scale Databases. Tremendous size of corpus of available data

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Manifold Learning on Probabilistic Graphical Models 概率图上的流形学习

Manifold Learning on Probabilistic Graphical Models 概率图上的流形学习. 答辩人 : 邵元龙导师 : 鲍虎军教授 & 何晓飞教授浙江大学 CAD&CG 国家重点实验室 2010 年 3 月 5 日. Outline. Background & Motivation Function Learning v.s. Statistical Modeling Manifold Regularized Variational Inference Algorithm Design & Examples

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Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. Authors: M. Belkin , P. Niyogi and V. Sindhwani Journal of Machine Learning Research, 2006 Presented by: Huy Tho Ho. Overview. Introduction Reproducing Kernel Hilbert Space

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Manifold learning

Manifold learning. Jan Kamenický. Nonlinear dimensionality reduction. Many features ⇒ many dimensions Dimensionality reduction Feature extraction (useful representation) Classification Visualization. Manifold learning. WhaT maniFold ?

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Modeling and Parallel Simulation of Multicore Architectures with Manifold

Modeling and Parallel Simulation of Multicore Architectures with Manifold. The Manifold Team. School of Electrical and Computer Engineering and School of Computer Science Georgia Institute of Technology Atlanta, GA. 30332. Sponsors. Motivation.

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Hodge Theory

Hodge Theory. Complex Manifolds. by William M. Faucette . Adapted from lectures by Mark Andrea A. Cataldo. Structure of Lecture . Conjugations Tangent bundles on a complex manifold Cotangent bundles on a complex manifold Standard orientation of a complex manifold

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Trap Manifold design

Trap Manifold design. Constraints The traps had to be able to withstand 300 degrees Celsius for at least 3 hours. The traps must be easily accessible. The traps need to be easily exchangeable.

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OXYGEN SENSORS

76. OXYGEN SENSORS. Figure 76-1 Many oxygen sensors are located in the exhaust manifold near its outlet so that the sensor can detect the presence or absence of oxygen in the exhaust stream for all cylinders that feed into the manifold.

699 views • 35 slides

Problems with Isomap, LLE and other Nonlinear Dimensionality Reduction Techniques

Problems with Isomap, LLE and other Nonlinear Dimensionality Reduction Techniques. Jonathan Huang ( jch1@cs.cmu.edu ) Advanced Perception 2006, CMU May 1 st , 2006. ISOMAP Algorithm Review. Connect each point to its k nearest neighbors to form a graph

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A Multi-resolution Topological Representation for Non-manifold Meshes

A Multi-resolution Topological Representation for Non-manifold Meshes. Leila De Floriani, Paola Magillo, Enrico Puppo, Davide Sobrero University of Genova Genova (Italy). Non-Manifold Multiresolution Modeling: Why Non-Manifold?.

489 views • 31 slides

Managed Pressure Operations NSD Manifold Flow Paths

Managed Pressure Operations NSD Manifold Flow Paths. NSD Manifold – Normal Drilling Flow Path. NSD Manifold – NSD Hose connected, line opened. NSD Manifold – Ball Valve closed, flowing through NSD Hose. NSD Ball Valve Closed. NSD Manifold – Flow through NSD Hose, Bleed Stand Pipe.

274 views • 11 slides

Similarities, Distances and Manifold Learning

Similarities, Distances and Manifold Learning. Prof. Richard C. Wilson Dept. of Computer Science University of York. Background. Typically objects are characterised by features Face images SIFT features Object spectra ... If we measure n features → n -dimensional space

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Non-Manifold Multi-Resolution Modeling

Non-Manifold Multi-Resolution Modeling. Geometric Modeling and Computer Graphics Group Department of Computer and Information Sciences University of Genova, Genova (Italy) http://www.disi.unige.it/person/DeflorianiL/. What does Non-Manifold Mean?.

346 views • 12 slides

Object Orie’d Data Analysis, Last Time

Object Orie’d Data Analysis, Last Time. Discrimination for manifold data (Sen) Simple Tangent plane SVM Iterated TANgent plane SVM Manifold SVM Interesting point: Analysis done really in the manifold Not just in projected tangent plane Deeper than Principal Geodesic Analysis?

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Manifold Learning: ISOMAP Alan O'Connor April 29, 2008

Manifold Learning: ISOMAP Alan O'Connor April 29, 2008. Manifold Learning. Dimensionality Reduction. Multidimensional Scaling. Convert a matrix of distances between vectors || x i – x j || in R n into a matrix of inner products.

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TUSTP 2003

TUSTP 2003. DOE Project: Design and Performance of Multiphase Distribution Manifold. By Angel Bustamante May 20, 2003. Topics. Introduction Objectives Experimental Program Manifold Design Future work. Introduction.

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Manifold learning: MDS and Isomap

Manifold learning: MDS and Isomap

Presentation Transcript

Modern Automotive Technology

4.2.11

HYDRAULICS_5

Modeling and Parallel Simulation of Multicore Systems with Manifold

LH2 Manifold R &amp; D

Richard G. Baraniuk Chinmay Hegde

Manifold Learning on Probabilistic Graphical Models 概率图上的流形学习

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

Manifold learning

Modeling and Parallel Simulation of Multicore Architectures with Manifold

Hodge Theory

Trap Manifold design

OXYGEN SENSORS

Problems with Isomap, LLE and other Nonlinear Dimensionality Reduction Techniques

A Multi-resolution Topological Representation for Non-manifold Meshes

Managed Pressure Operations NSD Manifold Flow Paths

Similarities, Distances and Manifold Learning

Non-Manifold Multi-Resolution Modeling

Object Orie’d Data Analysis, Last Time

Manifold Learning: ISOMAP Alan O'Connor April 29, 2008

TUSTP 2003

LH2 Manifold R & D