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09/18/2023
Multi-dimensional domain generalization with low-rank structures
In conventional statistical and machine learning methods, it is typicall...
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03/14/2022
A Focusing Framework for Testing Bi-Directional Causal Effects with GWAS Summary Data
Mendelian randomization (MR) is a powerful method that uses genetic vari...
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02/09/2022
Transferred Q-learning
We consider Q-learning with knowledge transfer, using samples from a tar...
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01/11/2022
Estimation and Inference with Proxy Data and its Genetic Applications
Existing high-dimensional statistical methods are largely established fo...
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01/02/2022
Improving Out-of-Distribution Robustness via Selective Augmentation
Machine learning algorithms typically assume that training and test exam...
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08/27/2021
Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach
The limited representation of minorities and disadvantaged populations i...
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07/28/2021
Performance Analysis of Dual-Hop THz Transmission Systems over α-μ Fading Channels with Pointing Errors
In this paper, the performance of a dual-hop relaying terahertz (THz) wi...
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06/08/2021
A Unified Approach to Robust Inference for Genetic Covariance
Genome-wide association studies (GWAS) have identified thousands of gene...
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11/18/2020
Performance Analysis of UAV-based Mixed RF-UWOC Transmission Systems
In this paper, we investigate the performance of a mixed radio-frequency...
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11/18/2020
On the Performance of RIS-Assisted Dual-Hop Mixed RF-UWOC Systems
In this paper, we investigate the performance of a reconfigurable intell...
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11/18/2020
Performance Analysis of Dual-Hop Mixed PLC/RF Communication Systems
In this paper, we study a dual-hop mixed power line communication and ra...
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10/21/2020
Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control
Transfer learning for high-dimensional Gaussian graphical models (GGMs) ...
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10/19/2020
Causal Inference for Nonlinear Outcome Models with Possibly Invalid Instrumental Variables
Instrumental variable methods are widely used for inferring the causal e...
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06/18/2020
Transfer Learning for High-dimensional Linear Regression: Prediction, Estimation, and Minimax Optimality
This paper considers the estimation and prediction of a high-dimensional...
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07/13/2019
Inference for high-dimensional linear mixed-effects models: A quasi-likelihood approach
Linear mixed-effects models are widely used in analyzing clustered or re...
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11/09/2017
