42 citations · 71 across the 19 of their papers we have counts for
11 papers · 1 filter
Fast Approximation of the Generalized Sliced-Wasserstein Distance
Dung Le, Huy Nguyen, Khai Nguyen +2
Generalized sliced Wasserstein distance is a variant of sliced Wasserstein distance that exploits the power of non-linear projection through a given defining function to better cap…
Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures
Tongzheng Ren, Fuheng Cui, Sujay Sanghavi +1
The Expectation-Maximization (EM) algorithm has been predominantly used to approximate the maximum likelihood estimation of the location-scale Gaussian mixtures. However, when the…
Improving Computational Complexity in Statistical Models with Second-Order Information
Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi +1
It is known that when the statistical models are singular, i.e., the Fisher information matrix at the true parameter is degenerate, the fixed step-size gradient descent algorithm t…
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…
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…