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20202026
most citedA Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques

22 citations · 26 across the 13 of their papers we have counts for

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10 papers · 1 filter

stat.ME2026

Linear regression with probabilistic networks for network-linked data

Jingnan Zhang, Shiwen Ye, Danyang Huang

Network-linked data combine a network with covariates and responses observed for its nodes. Common regression approaches either model dependence among neighboring responses using t…

stat.ME2026

Quantile Social Autoregressive Model

Liyuan Wang, Danyang Huang, Wei Lan +1

Research on modelling peer effects has predominantly relied on linear-in-means models. However, averaging peer responses prevents these models from capturing the effects of extreme…

stat.ME2025

Pseudo-Likelihood Ratio Screening based on Network Data with Applications

Wei Hu, Danyang Huang, Bo Zhang

Social network platforms today generate vast amounts of data, including network structures and a large number of user-defined tags, which reflect users' interests. The dimensionali…

stat.ME2024★ 1 cited

Distributed Pseudo-Likelihood Method for Community Detection in Large-Scale Networks

Jiayi Deng, Danyang Huang, Bo Zhang

This paper proposes a distributed pseudo-likelihood method (DPL) to conveniently identify the community structure of large-scale networks. Specifically, we first propose a block-wi…

stat.ME2024

Statistical Inference for Regression with Imputed Binary Covariates with Application to Emotion Recognition

Ziqian Lin, Danyang Huang, Ziyu Xiong +1

In the flourishing live streaming industry, accurate recognition of streamers' emotions has become a critical research focus, with profound implications for audience engagement and…

stat.ME2024★ 22 cited

A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques

Xuetong Li, Yuan Gao, Hong Chang +11

This paper presents a selective review of statistical computation methods for massive data analysis. A huge amount of statistical methods for massive data computation have been rap…

stat.ME2024

Bias-Correction for Privacy-Protected Spatial Autoregressive Models with Application to Restaurant Network Analysis

Danyang Huang, Ziyi Kong, Shuyuan Wu +1

Spatial autoregressive (SAR) models and their extensions are important tools for studying network effects. However, with an increasing emphasis on data privacy, data providers ofte…

stat.ME2023

Subsampling-Based Modified Bayesian Information Criterion for Large-Scale Stochastic Block Models

Jiayi Deng, Danyang Huang, Xiangyu Chang +1

Identifying the number of communities is a fundamental problem in community detection, which has received increasing attention recently. However, rapid advances in technology have…

stat.ME2022

A Wasserstein distance-based spectral clustering method for transaction data analysis

Yingqiu Zhu, Danyang Huang, Bo Zhang

With the rapid development of online payment platforms, it is now possible to record massive transaction data. Clustering on transaction data significantly contributes to analyzing…

stat.ME2020★ 1 cited

Efficient Estimation for Generalized Linear Models on a Distributed System with Nonrandomly Distributed Data

Feifei Wang, Danyang Huang, Yingqiu Zhu +1

Distributed systems have been widely used in practice to accomplish data analysis tasks of huge scales. In this work, we target on the estimation problem of generalized linear mode…