Search Results - "Shang, Zuofeng"

Distributed adaptive nearest neighbor classifier: algorithm and theory by Liu, Ruiqi, Xu, Ganggang, Shang, Zuofeng

“…When data is of an extraordinarily large size or physically stored in different locations, the distributed nearest neighbor (NN) classifier is an attractive…”
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Consistency of Bayesian linear model selection with a growing number of parameters by Shang, Zuofeng, Clayton, Murray K.

“…Linear models with a growing number of parameters have been widely used in modern statistics. One important problem about this kind of model is the variable…”
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Heterogeneous dense subhypergraph detection by Yuan, Mingao, Shang, Zuofeng

“…We study the problem of testing the existence of a heterogeneous dense subhypergraph. The null hypothesis corresponds to a heterogeneous Erdös–Rényi uniform…”
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NONPARAMETRIC INFERENCE IN GENERALIZED FUNCTIONAL LINEAR MODELS by Shang, Zuofeng, Cheng, Guang

“…We propose a roughness regularization approach in making nonparametric inference for generalized functional linear models. In a reproducing kernel Hubert space…”
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Vector sampling expansions in shift invariant subspaces by Shang, Zuofeng, Sun, Wenchang, Zhou, Xingwei

“…Multi-input multi-output (MIMO) sampling scheme which is motivated by applications in multi-channel deconvolution and multi-source separation has been…”
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LOCAL AND GLOBAL ASYMPTOTIC INFERENCE IN SMOOTHING SPLINE MODELS by Shang, Zuofeng, Cheng, Guang

“…This article studies local and global inference for smoothing spline estimation in a unified asymptotic framework. We first introduce a new technical tool…”
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Optimal nonparametric inference via deep neural network by Liu, Ruiqi, Boukai, Ben, Shang, Zuofeng

“…Deep neural network is a state-of-art method in modern science and technology. Much statistical literature have been devoted to understanding its performance…”
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Minimax optimal high‐dimensional classification using deep neural networks by Wang, Shuoyang, Shang, Zuofeng

“…High‐dimensional classification is a fundamentally important research problem in high‐dimensional data analysis. In this paper, we derive a nonasymptotic rate…”
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Information limits for detecting a subhypergraph by Yuan, Mingao, Shang, Zuofeng

“…We consider the problem of recovering a subhypergraph based on an observed adjacency tensor corresponding to a uniform hypergraph. The uniform hypergraph is…”
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JOINT ASYMPTOTICS FOR SEMI-NONPARAMETRIC REGRESSION MODELS WITH PARTIALLY LINEAR STRUCTURE by Cheng, Guang, Shang, Zuofeng

“…We consider a joint asymptotic framework for studying semi-nonparametric regression models where (finite-dimensional) Euclidean parameters and…”
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Deep neural network classifier for multidimensional functional data by Wang, Shuoyang, Cao, Guanqun, Shang, Zuofeng

“…We propose a new approach, called as functional deep neural network (FDNN), for classifying multidimensional functional data. Specifically, a deep neural…”
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Testing community structure for hypergraphs by Yuan, Mingao, Liu, Ruiqi, Feng, Yang, Shang, Zuofeng

“…Many complex networks in the real world can be formulated as hypergraphs where community detection has been widely used. However, the fundamental question of…”
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Nonparametric Testing under Randomized Sketching by Liu, Meimei, Shang, Zuofeng, Yang, Yun, Cheng, Guang

“…A common challenge in nonparametric inference is its high computational complexity when data volume is large. In this paper, we develop computationally…”
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A likelihood-ratio type test for stochastic block models with bounded degrees by Yuan, Mingao, Feng, Yang, Shang, Zuofeng

“…A fundamental problem in network data analysis is to test Erdös–Rényi model Gn,a+b2n versus a bisection stochastic block model Gn,an,bn, where a,b>0 are…”
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Distributed Generalized Cross-Validation for Divide-and-Conquer Kernel Ridge Regression and Its Asymptotic Optimality by Xu, Ganggang, Shang, Zuofeng, Cheng, Guang

“…Tuning parameter selection is of critical importance for kernel ridge regression. To date, a data-driven tuning method for divide-and-conquer kernel ridge…”
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Online statistical inference for parameters estimation with linear-equality constraints by Liu, Ruiqi, Yuan, Mingao, Shang, Zuofeng

“…Stochastic gradient descent (SGD) and projected stochastic gradient descent (PSGD) are scalable algorithms to compute model parameters in unconstrained and…”
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Statistical Inference on Panel Data Models: A Kernel Ridge Regression Method by Zhao, Shunan, Liu, Ruiqi, Shang, Zuofeng

“…We propose statistical inferential procedures for nonparametric panel data models with interactive fixed effects in a kernel ridge regression framework…”
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Optimal Classification for Functional Data by Wang, Shuoyang, Shang, Zuofeng, Cao, Guanqun, Liu, Jun S.

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Calibrating multi-dimensional complex ODE from noisy data via deep neural networks by Li, Kexuan, Wang, Fangfang, Liu, Ruiqi, Yang, Fan, Shang, Zuofeng

“…Ordinary differential equations (ODEs) are widely used to model complex dynamics that arise in biology, chemistry, engineering, finance, physics, etc…”
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Identification and estimation in panel models with overspecified number of groups by Liu, Ruiqi, Shang, Zuofeng, Zhang, Yonghui, Zhou, Qiankun

“…We propose a simple and fast approach to identify and estimate the unknown group structure in panel models by adapting the M-estimation method. We consider…”
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