Under Review (Statistics/Econometrics)

Semiparametric Shape-restricted Estimators for Nonparametric Regression
Kenta Takatsu, Tianyu Zhang, and Arun Kumar Kuchibhotla.
paper | code
2023
Doubly Robust Machine Learning for an Instrumental Variable Study of
Surgical Care for Cholecystitis
Kenta Takatsu, Alexander W. Levis, Edward Kennedy, Rachel Kelz, and Luke Keele.
paper
2023
Debiased Inference for a Covariate-Adjusted Regression Function
Kenta Takatsu and Ted Westling.
(Honorable mention for Best Student Paper at SLDS 2023) | paper | code
2023

Publication in Computer Science

U-Statistics for Importance-Weighted Variational Inference
Javier Burroni, Kenta Takatsu, Justin Domke, and Daniel Sheldon.
Transactions on Machine Learning Research | paper
2023
Learning from Discriminatory Training Data
Przemyslaw A. Grabowicz, Nicholas Perello, and Kenta Takatsu.
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society | paper
2023
Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty, Kenta Takatsu, David Jensen, and Vikash Mansinghka.
ICML | paper
2020
A General Framework for Counterfactual Learning-to-Rank
Aman Agarwal, Kenta Takatsu, Ivan Zaitsev, and Thorsten Joachims.
International ACM SIGIR | paper
2019