Search Results for author: Shujie Ma

Found 6 papers, 0 papers with code

Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information

no code implementations22 Mar 2024 Shujie Ma, Po-Yao Niu, Yichong Zhang, Yinchu Zhu

This paper investigates statistical inference for noisy matrix completion in a semi-supervised model when auxiliary covariates are available.

Matrix Completion

SleepEGAN: A GAN-enhanced Ensemble Deep Learning Model for Imbalanced Classification of Sleep Stages

no code implementations4 Jul 2023 Xuewei Cheng, Ke Huang, Yi Zou, Shujie Ma

Deep neural networks have played an important role in automatic sleep stage classification because of their strong representation and in-model feature transformation abilities.

Automatic Sleep Stage Classification Classification +5

Privacy-Preserving Community Detection for Locally Distributed Multiple Networks

no code implementations27 Jun 2023 Xiao Guo, Xiang Li, Xiangyu Chang, Shujie Ma

To remove the bias incurred by RR and the squared network matrices, we develop a two-step bias-adjustment procedure.

Clustering Community Detection +2

Causal Inference of General Treatment Effects using Neural Networks with A Diverging Number of Confounders

no code implementations15 Sep 2020 Xiaohong Chen, Ying Liu, Shujie Ma, Zheng Zhang

This paper considers a generalized optimization framework for efficient estimation of general treatment effects using artificial neural networks (ANNs) to approximate the unknown nuisance function of growing-dimensional confounders.

Causal Inference

Detecting Latent Communities in Network Formation Models

no code implementations7 May 2020 Shujie Ma, Liangjun Su, Yichong Zhang

This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed effects.

Clustering regression

Multivariate Functional Regression via Nested Reduced-Rank Regularization

no code implementations10 Mar 2020 Xiaokang Liu, Shujie Ma, Kun Chen

We propose a nested reduced-rank regression (NRRR) approach in fitting regression model with multivariate functional responses and predictors, to achieve tailored dimension reduction and facilitate interpretation/visualization of the resulting functional model.

Dimensionality Reduction regression

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