Divide-and-conquer

Online Two-Way Estimation and Inference via Linear Mixed-Effects Models

In this article, we tackle the estimation and inference problem of analyzing distributed streaming data that is collected continuously over multiple data sites. We propose an online two-way approach via linear mixed-effects models. We explicitly …

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.