Search Results for author: Xinsheng Zhang

Found 6 papers, 2 papers with code

Knowledge Transfer across Multiple Principal Component Analysis Studies

no code implementations12 Mar 2024 Zeyu Li, Kangxiang Qin, Yong He, Wang Zhou, Xinsheng Zhang

In the first step, we integrate the shared subspace information across multiple studies by a proposed method named as Grassmannian barycenter, instead of directly performing PCA on the pooled dataset.

Activity Recognition Transfer Learning

Robust Covariance Estimation for High-dimensional Compositional Data with Application to Microbial Communities Analysis

1 code implementation20 Apr 2020 Yong He, PengFei Liu, Xinsheng Zhang, Wang Zhou

We construct a Median-of-Means (MOM) estimator for the centered log-ratio covariance matrix and propose a thresholding procedure that is adaptive to the variability of individual entries.


Projected Estimation for Large-dimensional Matrix Factor Models

no code implementations23 Mar 2020 Long Yu, Yong He, Xin-bing Kong, Xinsheng Zhang

In this study, we propose a projection estimation method for large-dimensional matrix factor models with cross-sectionally spiked eigenvalues.


Large-dimensional Factor Analysis without Moment Constraints

1 code implementation14 Aug 2019 Yong He, Xinbing Kong, Long Yu, Xinsheng Zhang

Large-dimensional factor model has drawn much attention in the big-data era, in order to reduce the dimensionality and extract underlying features using a few latent common factors.


D$^2$-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios

no code implementations3 Apr 2019 Zhengping Che, Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye

Driving datasets accelerate the development of intelligent driving and related computer vision technologies, while substantial and detailed annotations serve as fuels and powers to boost the efficacy of such datasets to improve learning-based models.

An Extreme-Value Approach for Testing the Equality of Large U-Statistic Based Correlation Matrices

no code implementations11 Feb 2015 Cheng Zhou, Fang Han, Xinsheng Zhang, Han Liu

Theoretically, we develop a theory for testing the equality of U-statistic based correlation matrices.


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