4 citations · 4 across the 2 of their papers we have counts for
2 papers
stat.ME2024
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Lucile Ter-Minassian, Liran Szlak, Ehud Karavani +2
Interpretability and transparency are essential for incorporating causal effect models from observational data into policy decision-making. They can provide trust for the model in…
cs.LG2017★ 4 cited
Online Learning with Local Permutations and Delayed Feedback
Ohad Shamir, Liran Szlak
We propose an Online Learning with Local Permutations (OLLP) setting, in which the learner is allowed to slightly permute the \emph{order} of the loss functions generated by an adv…