4 citations · 4 across the 6 of their papers we have counts for
6 papers
High-Dimensional Dynamic Covariance Models with Random Forests
Shuguang Yu, Fan Zhou, Yingjie Zhang +2
This paper introduces a novel nonparametric method for estimating high-dimensional dynamic covariance matrices with multiple conditioning covariates, leveraging random forests and…
Enhancing Missing Data Imputation through Combined Bipartite Graph and Complete Directed Graph
Zhaoyang Zhang, Hongtu Zhu, Ziqi Chen +2
In this paper, we aim to address a significant challenge in the field of missing data imputation: identifying and leveraging the interdependencies among features to enhance missing…
Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation
Zhaoyang Zhang, Ziqi Chen, Qiao Liu +2
In this paper, we propose a novel framework, the Sampling-guided Heterogeneous Graph Neural Network (SHT-GNN), to effectively tackle the challenge of missing data imputation in lon…
Nodewise Loreg: Nodewise -penalized Regression for High-dimensional Sparse Precision Matrix Estimation
Hai Shu, Ziqi Chen, Yingjie Zhang +1
We propose Nodewise Loreg, a nodewise -penalized regression method for estimating high-dimensional sparse precision matrices. We establish its asymptotic properties, including…
Nearest-Neighbor Sampling Based Conditional Independence Testing
Shuai Li, Ziqi Chen, Hongtu Zhu +2
The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes…
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks
Hai Shu, Ronghua Shi, Qiran Jia +2
Deep neural networks (DNNs) have achieved great success in image classification, but can be very vulnerable to adversarial attacks with small perturbations to images. To improve ad…