no code implementations • 23 Feb 2022 • Xuhui Zhang, Jose Blanchet, Soumyadip Ghosh, Mark S. Squillante
In contrast, our study first illustrates the benefits of incorporating a natural geometric structure within a linear regression model, which corresponds to the generalized eigenvalue problem formed by the Gram matrices of both domains.
no code implementations • 25 Feb 2021 • Jose Blanchet, Fernando Hernandez, Viet Anh Nguyen, Markus Pelger, Xuhui Zhang
Imputation methods in time-series data often are applied to the full panel data with the purpose of training a model for a downstream out-of-sample task.
1 code implementation • NeurIPS 2020 • Viet Anh Nguyen, Xuhui Zhang, Jose Blanchet, Angelos Georghiou
We consider the parameter estimation problem of a probabilistic generative model prescribed using a natural exponential family of distributions.
no code implementations • 13 Sep 2020 • Jose Blanchet, Yang Kang, Jose Luis Montiel Olea, Viet Anh Nguyen, Xuhui Zhang
This paper shows that dropout training in Generalized Linear Models is the minimax solution of a two-player, zero-sum game where an adversarial nature corrupts a statistician's covariates using a multiplicative nonparametric errors-in-variables model.
no code implementations • 22 Jul 2016 • Xuhui Zhang, Kevin B. Korb, Ann E. Nicholson, Steven Mascaro
The causal discovery of Bayesian networks is an active and important research area, and it is based upon searching the space of causal models for those which can best explain a pattern of probabilistic dependencies shown in the data.