289 citations · 755 across the 23 of their papers we have counts for
24 papers
Sampling-Based Batch Sequential Design by Stein Variational Gradient Descent
Penghui Fu, Xiaoxian Ding, Chunlin Ji +2
Many real-world experimental design problems require a batch of experimental runs across stages, in which multiple points are selected and evaluated at each stage. However, most wo…
Nearest-Neighbor Non-Gaussian Processes for Geostatistical Modeling
Penghui Fu, Yuhan Dong, Jianhua Z. Huang
We develop a general class of nearest-neighbor non-Gaussian processes (NNnGP) for modeling geostatistical data. By introducing non-linear conditional mean functions into the Vecchi…
A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models
Rui Tuo, Shiyuan He, Arash Pourhabib +2
This paper develops a frequentist solution to the functional calibration problem, where the value of a calibration parameter in a computer model is allowed to vary with the value o…
Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent Neural Networks
Mohammadreza Armandpour, Brian Kidd, Yu Du +1
In this paper, we study the problem of blood glucose forecasting and provide a deep personalized solution. Predicting blood glucose level in people with diabetes has significant va…
Asymptotic Properties of Penalized Spline Estimators in Concave Extended Linear Models: Rates of Convergence
Jianhua Z. Huang, Ya Su
This paper develops a general theory on rates of convergence of penalized spline estimators for function estimation when the likelihood functional is concave in candidate functions…
Simultaneous inference of periods and period-luminosity relations for Mira variable stars
Shiyuan He, Zhenfeng Lin, Wenlong Yuan +2
The Period--Luminosity relation (PLR) of Mira variable stars is an important tool to determine astronomical distances. The common approach of estimating the PLR is a two-step proce…
Functional PCA with Covariate Dependent Mean and Covariance Structure
Fei Ding, Shiyuan He, David E. Jones +1
Incorporating covariates into functional principal component analysis (PCA) can substantially improve the representation efficiency of the principal components and predictive perfo…
Global Adversarial Attacks for Assessing Deep Learning Robustness
Hanbin Hu, Mit Shah, Jianhua Z. Huang +1
It has been shown that deep neural networks (DNNs) may be vulnerable to adversarial attacks, raising the concern on their robustness particularly for safety-critical applications.…
Near-infrared Mira Period-Luminosity Relations in M33
Wenlong Yuan, Lucas M. Macri, Atefeh Javadi +2
We analyze sparsely-sampled near-infrared (JHKs) light curves of a sample of 1781 Mira variable candidates in M33, originally discovered using I-band time-series observations. We e…
Safe Active Feature Selection for Sparse Learning
Shaogang Ren, Jianhua Z. Huang, Shuai Huang +1
We present safe active incremental feature selection~(SAIF) to scale up the computation of LASSO solutions. SAIF does not require a solution from a heavier penalty parameter as in…
Characterization of Type Ia Supernova Light Curves Using Principal Component Analysis of Sparse Functional Data
Shiyuan He, Lifan Wang, Jianhua Z. Huang
With growing data from ongoing and future supernova surveys it is possible to empirically quantify the shapes of SNIa light curves in more detail, and to quantitatively relate the…
To Wait or Not to Wait: Two-way Functional Hazards Model for Understanding Waiting in Call Centers
Gen Li, Jianhua Z. Huang, Haipeng Shen
Telephone call centers offer a convenient communication channel between businesses and their customers. Efficient management of call centers needs accurate modeling of customer wai…
Large Magellanic Cloud Near-Infrared Synoptic Survey. V. Period-Luminosity Relations of Miras
Wenlong Yuan, Lucas M. Macri, Shiyuan He +3
We study the near-infrared properties of 690 Mira candidates in the central region of the Large Magellanic Cloud, based on time-series observations at JHKs. We use densely-sampled…
The M33 Synoptic Stellar Survey. II. Mira Variables
Wenlong Yuan, Shiyuan He, Lucas M. Macri +2
We present the discovery of 1847 Mira candidates in the Local Group galaxy M33 using a novel semi-parametric periodogram technique coupled with a Random Forest classifier. The algo…
Adaptive Basis Selection for Exponential Family Smoothing Splines with Application in Joint Modeling of Multiple Sequencing Samples
Ping Ma, Nan Zhang, Jianhua Z. Huang +1
Second-generation sequencing technologies have replaced array-based technologies and become the default method for genomics and epigenomics analysis. Second-generation sequencing t…
Asymptotic properties of adaptive group Lasso for sparse reduced rank regression
Kejun He, Jianhua Z. Huang
This paper studies the asymptotic properties of the penalized least squares estimator using an adaptive group Lasso penalty for the reduced rank regression. The group Lasso penalty…
Period estimation for sparsely-sampled quasi-periodic light curves applied to Miras
Shiyuan He, Wenlong Yuan, Jianhua Z. Huang +2
We develop a non-linear semi-parametric Gaussian process model to estimate periods of Miras with sparsely-sampled light curves. The model uses a sinusoidal basis for the periodic v…
A Study of Functional Depths
James P. Long, Jianhua Z. Huang
Functional depth is used for ranking functional observations from most outlying to most typical. The ranks produced by functional depth have been proposed as the basis for function…
Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data
Guang Cheng, Lan Zhou, Jianhua Z. Huang
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be m…
Bayesian object classification of gold nanoparticles
Bledar A. Konomi, Soma S. Dhavala, Jianhua Z. Huang +5
The properties of materials synthesized with nanoparticles (NPs) are highly correlated to the sizes and shapes of the nanoparticles. The transmission electron microscopy (TEM) imag…
Robust regularized singular value decomposition with application to mortality data
Lingsong Zhang, Haipeng Shen, Jianhua Z. Huang
We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human…
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
Pinghua Gong, Changshui Zhang, Zhaosong Lu +2
Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over…
Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors
Huiyan Sang, Mikyoung Jun, Jianhua Z. Huang
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual m…
Bootstrap consistency for general semiparametric -estimation
Guang Cheng, Jianhua Z. Huang
Consider -estimation in a semiparametric model that is characterized by a Euclidean parameter of interest and an infinite-dimensional nuisance parameter. As a general purpose ap…