3 papers
stat.ML2024
C-Learner: Constrained Learning for Causal Inference
Tiffany Tianhui Cai, Yuri Fonseca, Kaiwen Hou +1
Debiasing methods such as augmented inverse propensity weighting (AIPW), and targeted maximum likelihood estimation (TMLE) enjoy asymptotic properties like semiparametric efficienc…
stat.ML2024
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
Yuri Fonseca, Caio Peixoto, Yuri Saporito
Instrumental variables (IVs) provide a powerful strategy for identifying causal effects in the presence of unobservable confounders. Within the nonparametric setting (NPIV), recent…
stat.ML2022
Statistical Learning and Inverse Problems: A Stochastic Gradient Approach
Yuri R. Fonseca, Yuri F. Saporito
Inverse problems are paramount in Science and Engineering. In this paper, we consider the setup of Statistical Inverse Problem (SIP) and demonstrate how Stochastic Gradient Descent…