9 citations · 12 across the 5 of their papers we have counts for
6 papers
You Only Compress Once: Optimal Data Compression for Estimating Linear Models
Jeffrey Wong, Eskil Forsell, Randall Lewis +2
Linear models are used in online decision making, such as in machine learning, policy algorithms, and experimentation platforms. Many engineering systems that use linear models ach…
Success Stories from a Democratized Experimentation Platform
Eskil Forsell, Julie Beckley, Simon Ejdemyr +5
We demonstrate the effectiveness of democratization and efficient computation as key concepts of our experimentation platform (XP) by presenting four new models supported by the pl…
Computational Causal Inference
Jeffrey C. Wong
We introduce computational causal inference as an interdisciplinary field across causal inference, algorithms design and numerical computing. The field aims to develop software spe…
Efficient Computation for Centered Linear Regression with Sparse Inputs
Jeffrey Wong
Regression with sparse inputs is a common theme for large scale models. Optimizing the underlying linear algebra for sparse inputs allows such models to be estimated faster. At the…
Efficient Computation of Linear Model Treatment Effects in an Experimentation Platform
Jeffrey Wong, Randall Lewis, Matthew Wardrop
Linear models are a core component for statistical software that analyzes treatment effects. They are used in experimentation platforms where analysis is automated, as well as scie…
Engineering for a Science-Centric Experimentation Platform
Nikos Diamantopoulos, Jeffrey Wong, David Issa Mattos +4
Netflix is an internet entertainment service that routinely employs experimentation to guide strategy around product innovations. As Netflix grew, it had the opportunity to explore…