1 citations · 3 across the 3 of their papers we have counts for
3 papers
stat.CO2018★ 1 cited
A Fast Divide-and-Conquer Sparse Cox Regression
Yan Wang, Nathan Palmer, Qian Di +3
We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size is exceedin…
cs.CL2018★ 1 cited
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data
Andrew L. Beam, Benjamin Kompa, Allen Schmaltz +6
Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this article, we present a new set of…
stat.ME2016★ 1 cited
Doubly robust matching estimators for high dimensional confounding adjustment
Joseph Antonelli, Matthew Cefalu, Nathan Palmer +1
Valid estimation of treatment effects from observational data requires proper control of confounding. If the number of covariates is large relative to the number of observations, t…