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ORCIDBenjamin Letham
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2020 – today
- 2024
[i13]Syrine Belakaria, Benjamin Letham, Janardhan Rao Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy:
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. CoRR abs/2407.09739 (2024)- 2023
- [c11]Stephen Keeley, Benjamin Letham, Craig Sanders, Chase Tymms, Michael Shvartsman:
A Semi-parametric Model for Decision Making in High-Dimensional Sensory Discrimination Tasks. AAAI 2023: 40-47 - [c10]Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy:
Sparse Bayesian optimization. AISTATS 2023: 3754-3774 - [c9]Phillip Guan
, Eric Penner, Joel Hegland, Benjamin Letham, Douglas Lanman:
Perceptual Requirements for World-Locked Rendering in AR and VR. SIGGRAPH Asia 2023: 35:1-35:10 - [i12]Phillip Guan, Eric Penner, Joel Hegland, Benjamin Letham, Douglas Lanman:
Perceptual Requirements for World-Locked Rendering in AR and VR. CoRR abs/2303.15666 (2023) - [i11]Mia Garrard, Hanson Wang, Ben Letham, Shaun Singh, Abbas Kazerouni, Sarah Tan, Zehui Wang, Yin Huang, Yichun Hu, Chad Zhou, Norm Zhou, Eytan Bakshy:
Practical Policy Optimization with Personalized Experimentation. CoRR abs/2303.17648 (2023) - [i10]Michael Shvartsman, Benjamin Letham, Stephen Keeley:
Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences. CoRR abs/2306.06296 (2023) - 2022
- [c8]Benjamin Letham, Phillip Guan, Chase Tymms, Eytan Bakshy, Michael Shvartsman:
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation. AISTATS 2022: 8493-8513 - [i9]Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy:
Sparse Bayesian Optimization. CoRR abs/2203.01900 (2022) - [i8]Benjamin Letham, Phillip Guan, Chase Tymms, Eytan Bakshy, Michael Shvartsman:
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation. CoRR abs/2203.09751 (2022) - 2020
- [c7]Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy:
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. NeurIPS 2020 - [c6]Qing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy:
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization. NeurIPS 2020 - [c5]Benjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy:
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization. NeurIPS 2020 - [i7]Benjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy:
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization. CoRR abs/2001.11659 (2020)
2010 – 2019
- 2019
- [j4]Benjamin Letham, Eytan Bakshy:
Bayesian Optimization for Policy Search via Online-Offline Experimentation. J. Mach. Learn. Res. 20: 145:1-145:30 (2019) - [i6]Benjamin Letham, Eytan Bakshy:
Bayesian Optimization for Policy Search via Online-Offline Experimentation. CoRR abs/1904.01049 (2019) - [i5]Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy:
BoTorch: Programmable Bayesian Optimization in PyTorch. CoRR abs/1910.06403 (2019) - 2018
- [i4]Matthias Feurer, Benjamin Letham, Eytan Bakshy:
Scalable Meta-Learning for Bayesian Optimization. CoRR abs/1802.02219 (2018) - 2017
- [i3]Benjamin Letham, Brian Karrer, Guilherme Ottoni, Eytan Bakshy:
Constrained Bayesian Optimization with Noisy Experiments. CoRR abs/1706.07094 (2017) - [i2]Sean J. Taylor, Benjamin Letham:
Forecasting at Scale. PeerJ Prepr. 5: e3190 (2017) - 2016
- [c4]Benjamin Letham, Lydia M. Letham, Cynthia Rudin:
Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts. KDD 2016: 1695-1704 - 2015
- [i1]Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan:
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model. CoRR abs/1511.01644 (2015) - 2014
- [c3]Benjamin Letham, Wei Sun, Anshul Sheopuri:
Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data. ICML 2014: 217-225 - 2013
- [j3]Benjamin Letham, Cynthia Rudin, Katherine A. Heller:
Growing a list. Data Min. Knowl. Discov. 27(3): 372-395 (2013) - [j2]Cynthia Rudin, Benjamin Letham, David Madigan:
Learning theory analysis for association rules and sequential event prediction. J. Mach. Learn. Res. 14(1): 3441-3492 (2013) - [j1]Benjamin Letham, Cynthia Rudin, David Madigan:
Sequential event prediction. Mach. Learn. 93(2-3): 357-380 (2013) - [c2]Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan:
An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis. AAAI (Late-Breaking Developments) 2013 - 2011
- [c1]Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan:
Sequential Event Prediction with Association Rules. COLT 2011: 615-634
Coauthor Index
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