Search Results - "Zhou, Xingcai"

Complete moment convergence of moving average processes under φ -mixing assumptions by Zhou, Xingcai

“…Let { Y i : − ∞ < i < ∞ } be a sequence of identically distributed φ -mixing random variables, and { a i : − ∞ < i < ∞ } an absolutely summable sequence of…”
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Asymptotics for L1-wavelet method for nonparametric regression by Zhou, Xingcai, Zhu, Fangxia

“…Wavelets are particularly useful because of their natural adaptive ability to characterize data with intrinsically local properties. When the data contain…”
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ADMM-Based Differential Privacy Learning for Penalized Quantile Regression on Distributed Functional Data by Zhou, Xingcai, Xiang, Yu

“…Alternating Direction Method of Multipliers (ADMM) is a widely used machine learning tool in distributed environments. In the paper, we propose an ADMM-based…”
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Communication-Efficient Distributed Learning for High-Dimensional Support Vector Machines by Zhou, Xingcai, Shen, Hao

“…Distributed learning has received increasing attention in recent years and is a special need for the era of big data. For a support vector machine (SVM), a…”
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Discussion of: 'A review of distributed statistical inference' by Lv, Shaogao, Zhou, Xingcai

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Wavelet-M-Estimation for Time-Varying Coefficient Time Series Models by Zhou, Xingcai, Zhu, Fangxia

“…This paper proposes wavelet-M-estimation for time-varying coefficient time series models by using a robust-type wavelet technique, which can adapt to local…”
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Distributed Bootstrap Simultaneous Inference for High-Dimensional Quantile Regression by Zhou, Xingcai, Jing, Zhaoyang, Huang, Chao

“…Modern massive data with enormous sample size and tremendous dimensionality are usually impossible to process with a single machine. They are typically stored…”
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Quantile-Wavelet Nonparametric Estimates for Time-Varying Coefficient Models by Zhou, Xingcai, Yang, Guang, Xiang, Yu

“…The paper considers quantile-wavelet estimation for time-varying coefficients by embedding a wavelet kernel into quantile regression. Our methodology is quite…”
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The Asymptotic Properties of Scad Penalized Generalized Linear Models with Adaptive Designs by Gao, Qibing, Zhu, Chunhua, Du, Xiuli, Zhou, Xingcai, Yin, Dingxin

“…This paper discusses the asymptotic properties of the SCAD (smoothing clipped absolute deviation) penalized quasi-likelihood estimator for generalized linear…”
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Uniform convergence rates for wavelet curve estimation in sup-norm loss by Zhou, Xingcai

“…This paper presents the rates of uniform strong consistency of wavelet estimation for nonparametric function in sup-norm loss by introducing an empirical…”
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Communication-efficient and privacy-preserving large-scale federated learning counteracting heterogeneity by Zhou, Xingcai, Yang, Guang

“…Federated learning is a commonly distributed framework for large-scale learning, where a model is learned over massively distributed remote devices without…”
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More communication-efficient distributed sparse learning by Zhou, Xingcai, Yang, Guang

“…In a modern distributed learning framework, the speeds of intra-worker calculation and inter-worker communication may differ by 1,000 times. It is advisable to…”
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The EM algorithm for the extended finite mixture of the factor analyzers model by Zhou, Xingcai, Liu, Xinsheng

“…This paper is devoted to extending common factors and categorical variables in the model of a finite mixture of factor analyzers based on the multivariate…”
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Maximum Likelihood Estimation of Tobit Factor Analysis for Multivariate t-Distribution by Zhou, Xingcai, Tan, Changchun

“…We propose multivariate tobit factor analysis models by assuming multivariate t-distribution error in tobit factor analysis. To circumvent direct calculation…”
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Communication-Efficient Nonconvex Federated Learning With Error Feedback for Uplink and Downlink by Zhou, Xingcai, Chang, Le, Cao, Jinde

“…Facing large-scale online learning, the reliance on sophisticated model architectures often leads to nonconvex distributed optimization, which is more…”
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Panel quantile regression neural network for electricity consumption forecasting in China: a new framework by Zhou, Xingcai, Wang, Jiangyan

“…Accurate electricity consumption forecasting (ECF) is challenging due to its complexity, and it is more challenging for a provincial ECF in China when it comes…”
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Communication-efficient and Byzantine-robust distributed learning with statistical guarantee by Zhou, Xingcai, Chang, Le, Xu, Pengfei, Lv, Shaogao

“…•Both communication efficiency and robustness for convex distributed learning are taken into accounts simultaneously, which is very rare in existing related…”
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Efficient Byzantine-robust distributed inference with regularization: A trade-off between compression and adversary by Zhou, Xingcai, Yang, Guang, Chang, Le, Lv, Shaogao

“…In large-scale distributed learning, the direct application of traditional inference is often not feasible, because it may contain multiple themes, such as…”
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Asymptotics for $L_{1}$-wavelet method for nonparametric regression by Zhou, Xingcai, Zhu, Fangxia

“…Wavelets are particularly useful because of their natural adaptive ability to characterize data with intrinsically local properties. When the data contain…”
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A general framework for quantile estimation with incomplete data by Han, Peisong, Kong, Linglong, Zhao, Jiwei, Zhou, Xingcai

“…Quantile estimation has attracted significant research interest in recent years. However, there has been only a limited literature on quantile estimation in…”
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