research
∙
06/09/2023
Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences
Models for human choice prediction in preference learning and psychophys...
share
research
∙
03/28/2023
Perceptual Requirements for World-Locked Rendering in AR and VR
Stereoscopic, head-tracked display systems can show users realistic, wor...
research
∙
03/18/2022
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation
Level set estimation (LSE) is the problem of identifying regions where a...
research
∙
03/03/2022
Sparse Bayesian Optimization
Bayesian optimization (BO) is a powerful approach to sample-efficient op...
research
∙
04/19/2021
Adaptive Nonparametric Psychophysics
We introduce a new set of models and adaptive psychometric testing metho...
research
∙
01/31/2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
Bayesian optimization (BO) is a popular approach to optimize expensive-t...
research
∙
10/14/2019
BoTorch: Programmable Bayesian Optimization in PyTorch
Bayesian optimization provides sample-efficient global optimization for ...
research
∙
04/01/2019
Bayesian Optimization for Policy Search via Online-Offline Experimentation
Online field experiments are the gold-standard way of evaluating changes...
research
∙
02/06/2018
Scalable Meta-Learning for Bayesian Optimization
Bayesian optimization has become a standard technique for hyperparameter...
research
∙
06/21/2017
Constrained Bayesian Optimization with Noisy Experiments
Randomized experiments are the gold standard for evaluating the effects ...
research
∙
11/05/2015