Author

Edgar Dobriban

University of Pennsylvania

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Review Aug 2026

Generalized Hierarchical Conformal Prediction

Many prediction problems arise with data collected in groups. In this setting, hierarchical conformal prediction (HCP) (Lee et al., 2026) provides distribution-free prediction sets for a new observation from a previously unseen group under hierarchical exchangeability. In many applications, however, prediction is condu...

Soham Mallick, E. Tchetgen, Edgar Dobriban et al. · 0 citations

Preprint Sep 2026

Improved Variance Estimation in Homoskedastic Nonparametric Random-Design Regression via a Two-Scale Approach

We study estimation of a constant conditional variance $\sigma^2$ in nonparametric regression with a $d$-dimensional random design. This is an important problem, and similar questions arise in causal inference. The regression function is $\beta_b$-H\"older smooth, the design density is $\beta_g$-H\"older smooth and bou...

Edgar Dobriban, Rajarshi Mukherjee, James M. Robins et al. · 1 citation

Preprint Aug 2026

Sharp Minimax Theory for Randomized Experiments

We study minimax-optimal designs and estimators for estimating the sample average treatment effect in finite population randomized experiments, where both design and estimator are unrestricted. For binary potential outcomes, we show this minimax risk is equivalent to the minimax risk $\rho_n^*$ of an estimation problem...

Timothy Sudijono, Edgar Dobriban, E. Tchetgen · 1 citation