Runze Li

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Penn State University ∙ University of California, Riverside

Professor at Penn State University

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Multiple-Splitting Projection Test for High-Dimensional Mean Vectors

We propose a multiple-splitting projection test (MPT) for one-sample mea...
10/29/2021 ∙ by Wanjun Liu, et al. ∙ 0 ∙ share

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Power-enhanced simultaneous test of high-dimensional mean vectors and covariance matrices with application to gene-set testing

Power-enhanced tests with high-dimensional data have received growing at...
09/30/2021 ∙ by Xiufan Yu, et al. ∙ 0 ∙ share

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Statistical Inference for Linear Mediation Models with High-dimensional Mediators and Application to Studying Stock Reaction to COVID-19 Pandemic

Mediation analysis draws increasing attention in many scientific areas s...
08/27/2021 ∙ by Xu Guo, et al. ∙ 0 ∙ share

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Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation

Gradient-based attention modeling has been used widely as a way to visua...
08/17/2021 ∙ by Runze Li, et al. ∙ 6 ∙ share

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Learning Local Recurrent Models for Human Mesh Recovery

We consider the problem of estimating frame-level full human body meshes...
07/27/2021 ∙ by Runze Li, et al. ∙ 2 ∙ share

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MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments

Self-supervised depth estimation for indoor environments is more challen...
07/26/2021 ∙ by Pan Ji, et al. ∙ 5 ∙ share

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Doubly Robust Feature Selection with Mean and Variance Outlier Detection and Oracle Properties

We propose a general approach to handle data contaminations that might d...
06/22/2021 ∙ by Luca Insolia, et al. ∙ 0 ∙ share

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A Distribution Free Conditional Independence Test with Applications to Causal Discovery

This paper is concerned with test of the conditional independence. We fi...
05/17/2021 ∙ by Zhanrui Cai, et al. ∙ 0 ∙ share

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Probabilistic HIV Recency Classification – A Logistic Regression without Labeled Individual Level Training Data

Accurate HIV incidence estimation based on individual recent infection s...
04/12/2021 ∙ by Ben Sheng, et al. ∙ 0 ∙ share

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Learning the aerodynamic design of supercritical airfoils through deep reinforcement learning

The aerodynamic design of modern civil aircraft requires a true sense of...
10/05/2020 ∙ by Runze Li, et al. ∙ 0 ∙ share

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Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection

We consider the stochastic contextual bandit problem under the high dime...
09/04/2020 ∙ by Yining Wang, et al. ∙ 5 ∙ share

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Estimation and Inference for the Mediation Effect in a Time-varying Mediation Model

Traditional mediation analysis typically examines the relations among an...
08/26/2020 ∙ by Xizhen Cai, et al. ∙ 0 ∙ share

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A Robust Consistent Information Criterion for Model Selection based on Empirical Likelihood

Conventional likelihood-based information criteria for model selection r...
06/23/2020 ∙ by Chixiang Chen, et al. ∙ 0 ∙ share

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A New Procedure for Controlling False Discovery Rate in Large-Scale t-tests

This paper is concerned with false discovery rate (FDR) control in large...
02/28/2020 ∙ by Changliang Zou, et al. ∙ 0 ∙ share

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Inference in High-Dimensional Linear Measurement Error Models

For a high-dimensional linear model with a finite number of covariates m...
01/28/2020 ∙ by Mengyan Li, et al. ∙ 0 ∙ share

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Central Limit Theorem for Linear Spectral Statistics of Large Dimensional Kendall's Rank Correlation Matrices and its Applications

This paper is concerned with the limiting spectral behaviors of large di...
12/13/2019 ∙ by Zeng Li, et al. ∙ 0 ∙ share

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Towards Visually Explaining Variational Autoencoders

Recent advances in Convolutional Neural Network (CNN) model interpretabi...
11/18/2019 ∙ by Wenqian Liu, et al. ∙ 84 ∙ share

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Model-free Feature Screening and FDR Control with Knockoff Features

This paper proposes a model-free and data-adaptive feature screening met...
08/19/2019 ∙ by Wanjun Liu, et al. ∙ 1 ∙ share

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Model-free Feature Screening with Projection Correlation and FDR Control with Knockoff Features

This paper proposes a model-free and data-adaptive feature screening met...
08/19/2019 ∙ by Wanjun Liu, et al. ∙ 0 ∙ share

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Distributed Feature Screening via Componentwise Debiasing

Feature screening is a powerful tool in the analysis of high dimensional...
03/09/2019 ∙ by Xingxiang Li, et al. ∙ 0 ∙ share

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On the Feasibility of Distributed Kernel Regression for Big Data

In modern scientific research, massive datasets with huge numbers of obs...
05/05/2015 ∙ by Chen Xu, et al. ∙ 0 ∙ share

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