XuanLong Nguyen
Wasserstein distances for discrete measures and convergence in nonparametric mixture models.
Fri, 09/16/2011 - 15:01 — SomNambulAuthors: XuanLong Nguyen
Subjects: Statistics
AbstractWe consider Wasserstein distance functionals for comparing between and
assessing the convergence of latent discrete measures, which serve as mixing
distributions in hierarchical and nonparametric mixture models. We explore the
space of discrete probability measures metrized by Wasserstein distances,
clarify the relationships between Wasserstein distances of mixing distributions
and $f$-divergence functionals such as Hellinger and Kullback-Leibler distances
on the space of mixture distributions.- Read more
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Graphically dependent and spatially varying Dirichlet process mixtures.
Wed, 01/06/2010 - 16:01 — SomNambulAuthors: XuanLong Nguyen
Subjects: Methodology
AbstractWe consider the problem of clustering grouped and functional data, which are
indexed by a covariate, and assessing the dependency of the clustered groups on
the covariate. We assume that each observation within a group is a draw from a
mixture model. The mixture components and the number of such components can
change with the covariate, and are assumed to be unknown a priori. In addition
to learning the "local" clusters within each group we also assume the existence
of "global clusters" indexed over the covariate domain when the observations
across the groups are jointly analyzed.
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