790 citations · 1.1k across the 16 of their papers we have counts for
17 papers
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…
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
Syrine Belakaria, Benjamin Letham, Janardhan Rao Doppa +3
We consider the problem of active learning for global sensitivity analysis of expensive black-box functions. Our aim is to efficiently learn the importance of different input varia…
Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences
Michael Shvartsman, Benjamin Letham, Stephen Keeley
Models for human choice prediction in preference learning and psychophysics often consider only binary response data, requiring many samples to accurately learn preferences or perc…
Practical Policy Optimization with Personalized Experimentation
Mia Garrard, Hanson Wang, Ben Letham +9
Many organizations measure treatment effects via an experimentation platform to evaluate the casual effect of product variations prior to full-scale deployment. However, standard e…
Perceptual Requirements for World-Locked Rendering in AR and VR
Phillip Guan, Eric Penner, Joel Hegland +2
Stereoscopic, head-tracked display systems can show users realistic, world-locked virtual objects and environments. However, discrepancies between the rendering pipeline and physic…
A Semi-Parametric Model for Decision Making in High-Dimensional Sensory Discrimination Tasks
Stephen Keeley, Benjamin Letham, Chase Tymms +2
Psychometric functions typically characterize binary sensory decisions along a single stimulus dimension. However, real-life sensory tasks vary along a greater variety of dimension…