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The Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data.
Shusen Liu
Peer-Timo Bremer
J. J. Jayaraman
Bei Wang
Brian Summa
Valerio Pascucci
Published in:
Comput. Graph. Forum (2016)
Keyphrases
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high dimensional data
subspace learning
nearest neighbor
low dimensional
high dimensional
dimensionality reduction
high dimensionality
data sets
data points
data analysis
subspace clustering
high dimensions
manifold learning
dimension reduction
nonlinear dimensionality reduction
low rank
input space
dimensional data
clustering high dimensional data
original data
similarity search
high dimensional spaces
linear discriminant analysis
high dimensional data sets
mr images
subspace clusters
variable selection
neural network
data mining
high dimensional datasets
database
learning algorithm
feature selection
lower dimensional
decision trees
pattern recognition
image data