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Dimensionality-Reduction Using Connectionist Networks.
Eric Saund
Published in:
IEEE Trans. Pattern Anal. Mach. Intell. (1989)
Keyphrases
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connectionist networks
dimensionality reduction
high dimensional data
high dimensional
pattern recognition
principal component analysis
high dimensionality
feature space
feature extraction
dynamical systems
input space
dimensionality reduction methods
data points
low dimensional
data representation
manifold learning
structure preserving
feature selection
pattern recognition and machine learning
random projections
linear discriminant analysis
sparse representation
linear projection
principal components
lower dimensional
neural network
nonlinear dimensionality reduction
graph embedding
monte carlo
machine learning