Shrinkage Estimators in Online Experiments. - Drew Dimmery; Eytan Bakshy; Jasjeet S. Sekhon (KDD, 2019)

Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints. - Samuel Daulton; Shaun Singh; Vashist Avadhanula; Drew Dimmery; Eytan Bakshy (CoRR, 2019)

Balanced Off-Policy Evaluation in General Action Spaces. - Arjun Sondhi; David Arbour; Drew Dimmery (AISTATS, 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)

Efficient Balanced Treatment Assignments for Experimentation. - David Arbour; Drew Dimmery; Anup B. Rao (AISTATS, 2021)

Designing Transportable Experiments Under S-admissability. - My Phan; David Arbour; Drew Dimmery; Anup B. Rao (AISTATS, 2021)

Permutation Weighting. - David Arbour; Drew Dimmery; Arjun Sondhi (ICML, 2021)

Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies. - Han Wu; Sarah Tan; Weiwei Li 006; Mia Garrard; Adam Obeng; Drew Dimmery; Shaun Singh; Hanson Wang; Daniel R. Jiang; Eytan Bakshy (CoRR, 2021)

Online Balanced Experimental Design. - David Arbour; Drew Dimmery; Tung Mai; Anup B. Rao (ICML, 2022)

Interpretable Personalized Experimentation. - Han Wu; Sarah Tan; Weiwei Li 006; Mia Garrard; Adam Obeng; Drew Dimmery; Shaun Singh; Hanson Wang; Daniel R. Jiang; Eytan Bakshy (KDD, 2022)

Subjective visualization experiences: impact of visual design and experimental design. - Laura Koesten; Drew Dimmery; Michael Gleicher; Torsten Möller (CoRR, 2023)

Calibration of Heterogeneous Treatment Effects in Randomized Experiments. - Yan Leng; Drew Dimmery (Inf. Syst. Res., 2024)