Ivana Malenica — accepted AI-conference papers

2024

Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters

Brian M Cho, Yaroslav Mukhin, Kyra Gan, Ivana Malenica

ICML 2024poster

When estimating target parameters in nonparametric models with nuisance parameters, substituting the unknown nuisances with nonparametric estimators can introduce "plug-in bias." Traditional methods addressing this suboptimal bias-variance trade-off rely on the influence function (IF) of the target…

Cited by 2 Source ↗PDF ↗Scholar ↗

2019

More Efficient Off-Policy Evaluation through Regularized Targeted Learning

Aurelien Bibaut, Ivana Malenica, Nikos Vlassis, Mark Van Der Laan

ICML 2019oral

We study the problem of off-policy evaluation (OPE) in Reinforcement Learning (RL), where the aim is to estimate the performance of a new policy given historical data that may have been generated by a different policy, or policies. In particular, we introduce a novel doubly-robust estimator for the…

Cited by 42 Source ↗PDF ↗Scholar ↗