no code implementations • 4 Mar 2024 • Dat Do, Linh Do, Scott A. McKinley, Jonathan Terhorst, XuanLong Nguyen
The dendrogram's construction is derived from the theory of convergence of the mixing measures, and as a result, we can both consistently select the true number of mixing components and obtain the pointwise optimal convergence rate for parameter estimation from the tree, even when the model parameters are only weakly identifiable.
no code implementations • 8 Dec 2022 • Dat Do, Linh Do, XuanLong Nguyen
We provide simulation studies and data illustrations, which shed some light on the parameter learning behavior found in several popular regression mixture models reported in the literature.
no code implementations • 5 Feb 2022 • Dat Do, Nhat Ho, XuanLong Nguyen
As we collect additional samples from a data population for which a known density function estimate may have been previously obtained by a black box method, the increased complexity of the data set may result in the true density being deviated from the known estimate by a mixture distribution.
no code implementations • 29 Oct 2021 • Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Phung
We study the label shift problem between the source and target domains in general domain adaptation (DA) settings.
no code implementations • 24 Aug 2021 • Khang Le, Dung Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho
When the metric is the inner product, which we refer to as inner product Gromov-Wasserstein (IGW), we demonstrate that the optimal transportation plans of entropic IGW and its unbalanced variant are (unbalanced) Gaussian distributions.
1 code implementation • 7 Feb 2021 • Jiacheng Zhu, Aritra Guha, Dat Do, Mengdi Xu, XuanLong Nguyen, Ding Zhao
We introduce a formulation of optimal transport problem for distributions on function spaces, where the stochastic map between functional domains can be partially represented in terms of an (infinite-dimensional) Hilbert-Schmidt operator mapping a Hilbert space of functions to another.