research
∙
06/27/2023
Wasserstein Generative Regression
In this paper, we propose a new and unified approach for nonparametric r...
share
research
∙
05/01/2023
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression
We study the properties of differentiable neural networks activated by r...
research
∙
10/18/2022
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction
We propose a nonparametric quantile regression method using deep neural ...
research
∙
07/21/2022
Deep Sufficient Representation Learning via Mutual Information
We propose a mutual information-based sufficient representation learning...
research
∙
07/21/2022
Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks
We propose a penalized nonparametric approach to estimating the quantile...
research
∙
08/10/2021
Statistical Inference in High-dimensional Generalized Linear Models with Streaming Data
In this paper we develop an online statistical inference approach for hi...
research
∙
07/21/2021
Robust Nonparametric Regression with Deep Neural Networks
In this paper, we study the properties of robust nonparametric estimatio...
research
∙
07/10/2021
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition
This paper considers the problem of nonparametric quantile regression un...
research
∙
06/10/2021
Online Debiased Lasso
We propose an online debiased lasso (ODL) method for statistical inferen...
research
∙
06/02/2021
Combining case-control studies for identifiability and efficiency improvement in logistic regression
Can two separate case-control studies, one about Hepatitis disease and t...
research
∙
05/01/2021
Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks
In this paper, we consider the problem of binary classification with a c...
research
∙
04/14/2021