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Deep Nets for Local Manifold Learning
Charles K. Chui
, Hrushikesh N. Mhaskar
*
*
Corresponding author for this work
Department of Mathematics
Research output
:
Contribution to journal
›
Journal article
›
peer-review
38
Citations (Scopus)
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Dive into the research topics of 'Deep Nets for Local Manifold Learning'. Together they form a unique fingerprint.
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Keyphrases
Target Function
100%
Deep Nets
100%
Local Manifold Learning
100%
Training Data
66%
Approximation Accuracy
33%
Optimization Techniques
33%
Backpropagation
33%
Error Bound
33%
Eigendecomposition
33%
Euclidean Space
33%
Out-of-sample Extension
33%
Function Approximation
33%
Deep Learning Algorithm
33%
Approximation Scheme
33%
Priori Errors
33%
Local Smoothness
33%
Local Coordinate System
33%
Preimage Problem
33%
Tubular Neighborhood
33%
Multi-layered Neural Networks
33%
A-priori Bounds
33%
Engineering
Deep Learning Method
100%
Error Bound
100%
Optimization Technique
100%
Eigen Decomposition
100%
Priori Error
100%
Local Coordinate System
100%
Computer Science
Manifold Learning
100%
Target Function
100%
Training Data
66%
Deep Learning Method
33%
Optimization Technique
33%
Neural Network
33%
Approximation (Algorithm)
33%
Classical Problem
33%
Function Approximation
33%
approximation scheme
33%
Local Coordinate System
33%
Mathematics
Manifold
100%
Training Data
40%
Neural Network
20%
Cube
20%
Error Bound
20%
Euclidean Space
20%
Deep Learning Method
20%
Pre-Image
20%
Approximation of Function
20%
Local Coordinate System
20%