3 citations · 5 across the 5 of their papers we have counts for
6 papers
Statistical Inference for Streamed Longitudinal Data
Lan Luo, Jingshen Wang, Emily C. Hector
Modern longitudinal data, for example from wearable devices, measures biological signals on a fixed set of participants at a diverging number of time points. Traditional statistica…
Online Causal Inference with Application to Near Real-Time Post-Market Vaccine Safety Surveillance
Xu Shi, Lan Luo
Streaming data routinely generated by mobile phones, social networks, e-commerce, and electronic health records present new opportunities for near real-time surveillance of the imp…
Parallel-and-stream accelerator for computationally fast supervised learning
Emily C. Hector, Lan Luo, Peter X. -K. Song
Two dominant distributed computing strategies have emerged to overcome the computational bottleneck of supervised learning with big data: parallel data processing in the MapReduce…
Statistical Inference in High-dimensional Generalized Linear Models with Streaming Data
Lan Luo, Ruijian Han, Yuanyuan Lin +1
In this paper we develop an online statistical inference approach for high-dimensional generalized linear models with streaming data for real-time estimation and inference. We prop…
Real-Time Regression Analysis of Streaming Clustered Data With Possible Abnormal Data Batches
Lan Luo, Ling Zhou, Peter X. -K. Song
This paper develops an incremental learning algorithm based on quadratic inference function (QIF) to analyze streaming datasets with correlated outcomes such as longitudinal data a…
Online Debiased Lasso for Streaming Data
Ruijian Han, Lan Luo, Yuanyuan Lin +1
We propose an online debiased lasso (ODL) method for statistical inference in high-dimensional linear models with streaming data. The proposed ODL consists of an efficient computat…