| A general framework for counterfactual learning-to-rank A Agarwal, K Takatsu, I Zaitsev, T Joachims Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 137 | 2019 |
| Causal inference using Gaussian processes with structured latent confounders S Witty, K Takatsu, D Jensen, V Mansinghka International Conference on Machine Learning, 10313-10323, 2020 | 28 | 2020 |
| Debiased inference for a covariate-adjusted regression function K Takatsu, T Westling Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2024 | 10 | 2024 |
| Doubly robust machine learning-based estimation methods for instrumental variables with an application to surgical care for cholecystitis K Takatsu, AW Levis, E Kennedy, R Kelz, L Keele Journal of the Royal Statistical Society Series A: Statistics in Society …, 2024 | 2* | 2024 |
| U-statistics for importance-weighted variational inference J Burroni, K Takatsu, J Domke, D Sheldon arXiv preprint arXiv:2302.13918, 2023 | 2 | 2023 |
| From isotonic to Lipschitz regression: a new interpolative perspective on shape-restricted estimation K Takatsu, T Zhang, AK Kuchibhotla arXiv preprint arXiv:2307.05732, 2024 | | 2024 |
| Generalized van Trees inequality: Local minimax bounds for non-smooth functionals and irregular statistical models K Takatsu, AK Kuchibhotla arXiv preprint arXiv:2405.06437, 2024 | | 2024 |
| Learning from Discriminatory Training Data P Grabowicz, N Perello, K Takatsu Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 752-763, 2023 | | 2023 |
| Causal Inference using Gaussian Processes with Structured Latent Confounders: Supplementary Materials S Witty, K Takatsu, D Jensen, V Mansinghka | | |
| Nonparametric causal inference with a continuous exposure T Westling, K Takatsu 2022 Fall Eastern Sectional Meeting, 0 | | |
Ted WestlingAssistant Professor, University of Massachusetts Amherst在 math.umass.edu 的电子邮件经过验证
