Drew Dimmery

According to our database, Drew Dimmery authored at least 11 papers between 2019 and 2023.

Collaborative distances:

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

2023

Subjective visualization experiences: impact of visual design and experimental design.

Laura Koesten, Drew Dimmery, Michael Gleicher, Torsten Möller

CoRR, 2023

2022

Interpretable Personalized Experimentation.

Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel R. Jiang, Eytan Bakshy

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Online Balanced Experimental Design.

David Arbour, Drew Dimmery, Tung Mai, Anup B. Rao

Proceedings of the International Conference on Machine Learning, 2022

2021

Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies.

Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel R. Jiang, Eytan Bakshy

CoRR, 2021

Permutation Weighting.

David Arbour, Drew Dimmery, Arjun Sondhi

Proceedings of the 38th International Conference on Machine Learning, 2021

Designing Transportable Experiments Under S-admissability.

My Phan, David Arbour, Drew Dimmery, Anup B. Rao

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Efficient Balanced Treatment Assignments for Experimentation.

David Arbour, Drew Dimmery, Anup B. Rao

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Real-world Video Adaptation with Reinforcement Learning.

Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy

CoRR, 2020

Balanced Off-Policy Evaluation in General Action Spaces.

Arjun Sondhi, David Arbour, Drew Dimmery

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints.

Samuel Daulton, Shaun Singh, Vashist Avadhanula, Drew Dimmery, Eytan Bakshy

CoRR, 2019

Shrinkage Estimators in Online Experiments.

Drew Dimmery, Eytan Bakshy, Jasjeet S. Sekhon

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019