Manifold Learning

Jan 06, 2020

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Manifold Learning. Manifold Learning. Locally Linear Embedding (LLE). Arranging words : Each word was initially represented by a high-dimensional vector that counted the number of times it appeared in different encyclopedia articles. Words with similar contexts are collocated.

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Manifold Learning

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Manifold Learning
Manifold Learning
Locally Linear Embedding (LLE)
Arranging words: Each word was initially represented by a high-dimensional vector that counted the number of times it appeared in different encyclopedia articles. Words with similar contexts are collocated

Manifold - Lab 1

Manifold - Lab 1. In this lecture we will discuss about: Setting Manifold environment Compiling/running programs. Giorgos Hadjipollas. Summary. Setting manifold environment How to compile/run manifold programs Compiling/running HelloWorld program. How to compile/run manifold programs.

258 views • 4 slides

Manifold Learning Using Geodesic Entropic Graphs

Manifold Learning Using Geodesic Entropic Graphs. Research supported in part by: ARO-DARPA MURI DAAD19-02-1-0262. Alfred O. Hero and Jose Costa Dept. EECS, Dept Biomed. Eng., Dept. Statistics University of Michigan - Ann Arbor hero@eecs.umich.edu http://www.eecs.umich.edu/~hero.

537 views • 20 slides

Manifold learning: Laplacian Eigenmaps

Overview. Isomap and LLELocal geometry derived from k-nearest neighborsrequire dense data points on the manifold for good estimationIsomapGlobal approachPreserve the Geodesic distanceLLELocal approachPreserve linear combination weights. Outline of lecture. Laplacian EigenmapsProblem defini

835 views • 24 slides

Manifold Topics

Manifold Topics. Infra Mechanical and Thermal Team. Glenn Charest & John Fernandes. Data Center Source Liquid. What Δ T ranges or flow rates does the solution need to support? What liquid types need to be supported?

272 views • 11 slides

Dictionary Learning on a Manifold

Dictionary Learning on a Manifold. 1 Mingyuan Zhou, 2 Hongxia Yang, 3 Guillermo Sapiro, 2 David Dunson and 1 Lawrence Carin 1 Department of Electrical & Computer Engineering, Duke University 2 Department of Statistical Science, Duke University

395 views • 20 slides

Manifold learning: MDS and Isomap

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

616 views • 32 slides

Manifold Learning Via Homology

Manifold Learning Via Homology. Presenter: Ronen Talmon Topological Methods in Electrical Engineering and Networks January 19, 2011. Sources.

579 views • 36 slides

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 ?

1k views • 26 slides

Manifold Parameterization

Manifold Parameterization. Lei Zhang, Ligang Liu, Zhongping Ji, Guojin Wang Department of Mathematics Zhejiang University Accepted as regular paper by CGI2006. Overview. Parameterization Least-squares Mesh Manifold Parameterization “ Similar destination, different way ”

726 views • 47 slides

Manifold learning

Manifold learning. Xin Yang. Outline. Manifold and Manifold Learning Classical Dimensionality Reduction Semi-Supervised Nonlinear Dimensionality Reduction Experiment Results Conclusions. What is a manifold?. Examples: sphere and torus. Why we need manifold?. Manifold learning.

609 views • 29 slides

Manifold learning: Locally Linear Embedding

Manifold learning: Locally Linear Embedding. Jieping Ye Department of Computer Science and Engineering Arizona State University http://www.public.asu.edu/~jye02. Review: MDS. Metric scaling (classical MDS) assuming D is the squared distance matrix. Non-metric scaling

794 views • 23 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

1.02k views • 80 slides

Topology in Manifold Learning

Topology in Manifold Learning. Jonathan Huang Presented at misc-read, 11.22.06. Bibliography. *Simultaneous Inference of View and Body Pose Using Torus Manifolds* Chan-Su Lee and Ahmed Elgammal The 18 th International Conference on Pattern Recognition (ICPR), Hong Kong, August 21-24, 2006

1.28k views • 37 slides

Filter manifold

Whitecliff Farm Water System 1 of 3: Filtration schematic. Bypass. Pre-filter. Filter manifold. Control unit. Iron-manganese filter. Holding tank. Aeration tank. SO2 vent. To storage tanks. Backwash overflow. Cutoff valve. Primary flow. From well. Bypass & overflow.

216 views • 3 slides

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.

239 views • 11 slides

Manifold learning: MDS and Isomap

Manifold learning: MDS and Isomap. Manifold learning. A manifold is a topological space which is locally Euclidean. Manifold learning. A global geometric framework for nonlinear dimensionality reduction Tenenbaum JB, de Silva V., and Langford JC Science, 290: 2319–2323, 2000

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Manifold learning: Locally Linear Embedding

717 views • 24 slides

Lecture 13-14 Face Recognition – Subspace/Manifold Learning

EE4-62 MLCV. Lecture 13-14 Face Recognition – Subspace/Manifold Learning. Tae-Kyun Kim. EE4-62 MLCV. Face Recognition Applications. Applications include Automatic face tagging at commercial weblogs Face image retrieval in MPEG7 (our solution is MPEG7 standard)

601 views • 41 slides

Manifold Hydraulics

Manifold Hydraulics. Cayuga Lake Ithaca WWTP Outfall. Manifolds. Examples Sprinkler and drip irrigation systems wastewater discharge (multiport diffuser) Design objectives distribute a given discharge through multiple ports

544 views • 27 slides

Manifold learning: Locally Linear Embedding

424 views • 23 slides

Manifold Hydraulics

305 views • 27 slides

Manifold Learning

Manifold Learning. Kai Yang sadoii@163.com. 1.12.2015. Machine Learning Problem. (Training Data). f. C 罗. We always think X and Y are in Euclidean space. f:X → Y. Outline. What’s manifold and manifold learning? What’s classical methods and its application? Summary and thought.

338 views • 30 slides

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