would lie, such as Locally Linear Embedding (LLE) (Roweis and Saul, 2000), Isomap (Tenenbaum, ¨ de Silva and Langford, 2000), kernel Principal Components Analysis (PCA) (Sch olkopf, Smola and M¨ ller, 1998), ...
de silva
dimensionality reduction
factor analyzers
generalization
ghahramani
input object
kernel methods
langford
learning
manifold
mixtures
neighborhood relations
parametric methods
parametric models
parzen windows
principal components analysis
probabilistic pca
smola
tangent
tangent directions
tenenbaum
vertex