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

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)

Neural Pseudo-Label Optimism for the Bank Loan Problem. - Aldo Pacchiano; Shaun Singh; Edward Chou; Alexander C. Berg; Jakob N. Foerster (NeurIPS, 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)

Looper: An End-to-End ML Platform for Product Decisions. - Igor L. Markov; Hanson Wang; Nitya S. Kasturi; Shaun Singh; Mia R. Garrard; Yin Huang; Sze Wai Celeste Yuen; Sarah Tran; Zehui Wang; Igor Glotov; Tanvi Gupta; Peng Chen; et al. (KDD, 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)

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)

Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank Loan Problem. - Elena Gal; Shaun Singh; Aldo Pacchiano; Ben Walker; Terry J. Lyons; Jakob N. Foerster (CoRR, 2023)