47 citations · 153 across the 28 of their papers we have counts for
4 papers · 1 filter
Evaluating for the long term: Learnings from industry
Leif Sigerson, Tom Cunningham, Winston Chou +22
Online platforms prioritize long-term business outcomes, yet typical experiments are far too short to measure these outcomes directly. Our goal in this paper is to collect and shar…
Offline-to-Online Creative Optimization with Generative Models and Adaptive Testing
Kevin Lee, Benjamin Letham, Zhiyuan Jerry Lin +5
Ad creative optimization is increasingly constrained by evaluation rather than generation. Generative models can produce many plausible creatives, but reliable evaluation requires…
Pitfalls and Remedies for Multi-Task Bayesian Optimization
Carl Hvarfner, Sam Daulton, Max Balandat +1
Bayesian optimization routinely warm-starts a target experiment with data from related source tasks, and the multi-task Gaussian process is the textbook surrogate for the job. We r…
Empirical Gaussian Processes
Jihao Andreas Lin, Sebastian Ament, Louis C. Tiao +3
Gaussian processes (GPs) are powerful and widely used probabilistic regression models, but their effectiveness in practice is often limited by the choice of kernel function. This k…