42 citations · 73 across the 20 of their papers we have counts for
6 papers · 1 filter
Multivariate Smoothing via the Fourier Integral Theorem and Fourier Kernel
Nhat Ho, Stephen G. Walker
Starting with the Fourier integral theorem, we present natural Monte Carlo estimators of multivariate functions including densities, mixing densities, transition densities, regress…
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
Khai Nguyen, Son Nguyen, Nhat Ho +2
Relational regularized autoencoder (RAE) is a framework to learn the distribution of data by minimizing a reconstruction loss together with a relational regularization on the laten…
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
We study the convergence rates of the EM algorithm for learning two-component mixed linear regression under all regimes of signal-to-noise ratio (SNR). We resolve a long-standing q…
Uniform Convergence Rates for Maximum Likelihood Estimation under Two-Component Gaussian Mixture Models
Tudor Manole, Nhat Ho
We derive uniform convergence rates for the maximum likelihood estimator and minimax lower bounds for parameter estimation in two-component location-scale Gaussian mixture models w…
Distributional Sliced-Wasserstein and Applications to Generative Modeling
Khai Nguyen, Nhat Ho, Tung Pham +1
Sliced-Wasserstein distance (SW) and its variant, Max Sliced-Wasserstein distance (Max-SW), have been used widely in the recent years due to their fast computation and scalability…
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm
Khiem Pham, Khang Le, Nhat Ho +2
We provide a computational complexity analysis for the Sinkhorn algorithm that solves the entropic regularized Unbalanced Optimal Transport (UOT) problem between two measures of po…