Benjamin Letham

According to our database, Benjamin Letham authored at least 22 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences.

Michael Shvartsman, Benjamin Letham, Stephen Keeley

CoRR, 2023

Practical Policy Optimization with Personalized Experimentation.

Mia Garrard, Hanson Wang, Ben Letham, Shaun Singh, Abbas Kazerouni, Sarah Tan, Zehui Wang, Yin Huang, Yichun Hu, Chad Zhou, Norm Zhou, Eytan Bakshy

CoRR, 2023

Perceptual Requirements for World-Locked Rendering in AR and VR.

Phillip Guan, Eric Penner, Joel Hegland, Benjamin Letham, Douglas Lanman

Proceedings of the SIGGRAPH Asia 2023 Conference Papers, 2023

Sparse Bayesian optimization.

Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

A Semi-parametric Model for Decision Making in High-Dimensional Sensory Discrimination Tasks.

Stephen Keeley, Benjamin Letham, Craig Sanders, Chase Tymms, Michael Shvartsman

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation.

Benjamin Letham, Phillip Guan, Chase Tymms, Eytan Bakshy, Michael Shvartsman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization.

Benjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization.

Qing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization.

Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Bayesian Optimization for Policy Search via Online-Offline Experimentation.

Benjamin Letham, Eytan Bakshy

J. Mach. Learn. Res., 2019

BoTorch: Programmable Bayesian Optimization in PyTorch.

Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy

CoRR, 2019

2018

Scalable Meta-Learning for Bayesian Optimization.

Matthias Feurer, Benjamin Letham, Eytan Bakshy

CoRR, 2018

2017

Forecasting at Scale.

Sean J. Taylor, Benjamin Letham

PeerJ Prepr., 2017

Constrained Bayesian Optimization with Noisy Experiments.

Benjamin Letham, Brian Karrer, Guilherme Ottoni, Eytan Bakshy

CoRR, 2017

2016

Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts.

Benjamin Letham, Lydia M. Letham, Cynthia Rudin

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model.

Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan

CoRR, 2015

2014

Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data.

Benjamin Letham, Wei Sun, Anshul Sheopuri

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Sequential event prediction.

Benjamin Letham, Cynthia Rudin, David Madigan

Mach. Learn., 2013

Learning theory analysis for association rules and sequential event prediction.

Cynthia Rudin, Benjamin Letham, David Madigan

J. Mach. Learn. Res., 2013

Growing a list.

Benjamin Letham, Cynthia Rudin, Katherine A. Heller

Data Min. Knowl. Discov., 2013

An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis.

Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan

Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

2011

Sequential Event Prediction with Association Rules.

Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan

Proceedings of the COLT 2011, 2011