online learning

Online inference with debiased stochastic gradient descent

We propose a debiased stochastic gradient descent algorithm for online statistical inference with high-dimensional data. Our approach combines the debiasing technique developed in high-dimensional statistics with the stochastic gradient descent …


An online estimation and inference framework for streamed longitudinal data analysis (SLA).

Statistical Inference for Streamed Longitudinal Data

Modern longitudinal data, for example from wearable devices, measure biological signals on a fixed set of participants at a diverging number of time points. Traditional statistical methods are not equipped to handle the computational burden of …

Parallel-and-Stream Accelerator for Computationally Fast Supervised Learning

Two dominant distributed computing strategies have emerged to overcome the computational bottleneck of supervised learning with big data: parallel data processing in the MapReduce paradigm and serial data processing in the online streaming paradigm. …

Online MEM

An online two-way updating framework via mixed effects models to account for both within-site correlation and cross-site heterogeneity.

Renewable Estimation and Incremental Inference in Generalized Linear Models with Streaming Datasets

This paper presents an incremental updating algorithm to analyze streaming datasets using generalized linear models. The proposed method is formulated within a new framework of renewable estimation and incremental inference, in which the estimates …


A new framework of real-time estimation and incremental inference in generalized linear models with cross-sectional data streams.