22 citations · 23 across the 9 of their papers we have counts for
9 papers
Adaptive Decentralized Federated Learning for Robust Optimization
Shuyuan Wu, Feifei Wang, Yuan Gao +2
In decentralized federated learning (DFL), the presence of abnormal clients, often caused by noisy or poisoned data, can significantly disrupt the learning process and degrade the…
Doubly Smoothed Density Estimation with Application on Miners' Unsafe Act Detection
Qianhan Zeng, Miao Han, Ke Xu +2
We study anomaly detection in images under a fixed-camera environment and propose a \emph{doubly smoothed} (DS) density estimator that exploits spatial structure to improve estimat…
Auxiliary Learning and its Statistical Understanding
Hanchao Yan, Feifei Wang, Chuanxin Xia +1
Modern statistical analysis often encounters high-dimensional problems but with a limited sample size. It poses great challenges to traditional statistical estimation methods. In t…
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…
Subnetwork Estimation for Spatial Autoregressive Models in Large-scale Networks
Xuetong Li, Feifei Wang, Wei Lan +1
Large-scale networks are commonly encountered in practice (e.g., Facebook and Twitter) by researchers. In order to study the network interaction between different nodes of large-sc…
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator
Haobo Qi, Feifei Wang, Hansheng Wang
We study here a fixed mini-batch gradient decent (FMGD) algorithm to solve optimization problems with massive datasets. In FMGD, the whole sample is split into multiple non-overlap…
Improved Naive Bayes with Mislabeled Data
Qianhan Zeng, Yingqiu Zhu, Xuening Zhu +5
Labeling mistakes are frequently encountered in real-world applications. If not treated well, the labeling mistakes can deteriorate the classification performances of a model serio…
Testing Sufficiency for Transfer Learning
Ziqian Lin, Yuan Gao, Feifei Wang +1
Modern statistical analysis often encounters high dimensional models but with limited sample sizes. This makes the target data based statistical estimation very difficult. Then how…
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…