-
certain other methods that
perform well in such
settings (e.g.,
Laplacian Eigenmaps, LLE) as
special cases of
kernel PCA by
constructing a data-dependent...
-
Dimension Reduction and Data
Representation in
Breast CADx with
Laplacian Eigenmaps and t-SNE".
Medical Physics. 37 (1): 339–351. doi:10.1118/1.3267037. PMC 2807447...
- such as Isomap,
locally linear embedding (LLE),
Hessian LLE,
Laplacian eigenmaps, and
methods based on
tangent space analysis.
These techniques construct...
- He
wrote more than 90
academic publications and two books.
Laplacian eigenmaps "Niyogi, Partha, Obituary".
University of Chicago.
Archived from the original...
- (distance
metric learning)
using kernel PCA,
diffusion maps,
Laplacian eigenmaps,
local linear embedding,
locally preserving projections, and Sammon's...
- Alignment,
Multidimensional Scaling, Isomap,
Diffusion Maps,
Laplacian Eigenmaps Online learning algorithms such as SGD-QN,
Vowpal Wabbit Clustering algorithms:...
- doi:10.2307/2333955. JSTOR 2333955. Belkin, M; P
Niyogi (2003). "Laplacian
eigenmaps for
dimensionality reduction and data representation" (PDF).
Neural Com****tion...
-
LOBPCG to
scale spectral clustering and
manifold learning via
Laplacian eigenmaps to
large data sets.
NVIDIA has
implemented LOBPCG in its
nvGRAPH library...
