The A/B Testing Problem. - Eduardo M. Azevedo; Alex Deng; Jose Luis Montiel Olea; Justin Rao; E. Glen Weyl (EC, 2018)

Competing Models. - Jose Luis Montiel Olea; Pietro Ortoleva; Mallesh M. Pai; Andrea Prat (CoRR, 2019)

Machine Learning's Dropout Training is Distributionally Robust Optimal. - Jose H. Blanchet; Yang Kang; Jose Luis Montiel Olea; Viet Anh Nguyen; Xuhui Zhang (CoRR, 2020)

On the Robustness to Misspecification of α-posteriors and Their Variational Approximations. - Marco Avella-Medina; José Luis Montiel Olea; Cynthia Rush; Amilcar Velez (J. Mach. Learn. Res., 2022)

The A/B testing problem with Gaussian priors. - Eduardo M. Azevedo; David Mao; José Luis Montiel Olea; Amilcar Velez (J. Econ. Theory, 2023)

Dropout Training is Distributionally Robust Optimal. - Jose H. Blanchet; Yang Kang; José Luis Montiel Olea; Viet Anh Nguyen; Xuhui Zhang (J. Mach. Learn. Res., 2023)

Epsilon-Minimax Solutions of Statistical Decision Problems via the Hedge Algorithm. - Andres Aradillas Fernandez; Jose H. Blanchet; José Luis Montiel Olea; Chen Qiu; Jörg Stoye; Lezhi Tan (EC, 2025)

Externally Valid Selection of Experimental Sites via the k-Median Problem. - José Luis Montiel Olea; Brenda Prallon; Chen Qiu; Jörg Stoye; Yiwei Sun (EC, 2025)