67 citations · 82 across the 8 of their papers we have counts for
8 papers
A Grammar of Data Analysis
Xunmo Yang, Taylor Pospisil, Omkar Muralidharan +1
This paper outlines a grammar of data analysis, as distinct from grammars of data manipulation, in which the primitives are metrics and dimensions. We describe a Python implementat…
Empirical Bayes mean estimation with nonparametric errors via order statistic regression on replicated data
Nikolaos Ignatiadis, Sujayam Saha, Dennis L. Sun +1
We study empirical Bayes estimation of the effect sizes of units from noisy observations on each unit. We show that it is possible to achieve near-Bayes optimal mean square…
Second Order Calibration: A Simple Way to Get Approximate Posteriors
Omkar Muralidharan, Amir Najmi
Many large-scale machine learning problems involve estimating an unknown parameter for each of many items. For example, a key problem in sponsored search is to estimate the…
Teaching Statistics at Google Scale
Nicholas Chamandy, Omkar Muralidharan, Stefan Wager
Modern data and applications pose very different challenges from those of the 1950s or even the 1980s. Students contemplating a career in statistics or data science need to have th…
Feedback Detection for Live Predictors
Stefan Wager, Nick Chamandy, Omkar Muralidharan +1
A predictor that is deployed in a live production system may perturb the features it uses to make predictions. Such a feedback loop can occur, for example, when a model that predic…
On Calibrated Predictions for Auction Selection Mechanisms
H. Brendan McMahan, Omkar Muralidharan
Calibration is a basic property for prediction systems, and algorithms for achieving it are well-studied in both statistics and machine learning. In many applications, however, the…