59 citations · 180 across the 28 of their papers we have counts for
28 papers
Covariance Estimators for the ROOT-SGD Algorithm in Online Learning
Yiling Luo, Xiaoming Huo, Yajun Mei
Online learning naturally arises in many statistical and machine learning problems. The most widely used methods in online learning are stochastic first-order algorithms. Among thi…
Adaptive Partially-Observed Sequential Change Detection and Isolation
Xinyu Zhao, Jiuyun Hu, Yajun Mei +1
High-dimensional data has become popular due to the easy accessibility of sensors in modern industrial applications. However, one specific challenge is that it is often not easy to…
Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection
Jiuyun Hu, Yajun Mei, Sarah Holte +1
In this paper, we present an efficient statistical method (denoted as "Adaptive Resources Allocation CUSUM") to robustly and efficiently detect the hotspot with limited sampling re…
Cost-Efficient Fixed-Width Confidence Intervals for the Difference of Two Bernoulli Proportions
Ignacio Erazo, David Goldsman, Yajun Mei
We study properties of confidence intervals (CIs) for the difference of two Bernoulli distributions' success parameters, , in the case where the goal is to obtain a CI o…
Hot-spots Detection in Count Data by Poisson Assisted Smooth Sparse Tensor Decomposition
Yujie Zhao, Xiaoming Huo, Yajun Mei
Count data occur widely in many bio-surveillance and healthcare applications, e.g., the numbers of new patients of different types of infectious diseases from different cities/coun…
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models
Yiling Luo, Xiaoming Huo, Yajun Mei
We study the Stochastic Gradient Descent (SGD) algorithm in nonparametric statistics: kernel regression in particular. The directional bias property of SGD, which is known in the l…