27 citations · 134 across the 39 of their papers we have counts for
5 papers · 1 filter
A Hierarchy of Policy Learning Problems
Hamsa Bastani, Osbert Bastani, Shihan Chen
Policy learning has received substantial attention with the goal of learning policies from observational data for decision-making. A majority of work in this space has focused on d…
Learning to target with network interference
Xiaomeng Wang, Hamsa Bastani, Osbert Bastani +1
This paper studies adaptive targeting under network interference in a bandit setting, where treatments applied to one individual may affect others through spillover effects. We con…
Winner's Curse Drives False Promises in Data-Driven Decisions: A Case Study in Refugee Matching
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
A major challenge in data-driven decision-making is accurate policy evaluation-i.e., guaranteeing that a learned decision-making policy achieves the promised benefits. A popular st…
Beating the Winner's Curse via Inference-Aware Policy Optimization
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
There has been a surge of recent interest in automatically learning policies to target treatment decisions based on rich individual covariates. In addition, practitioners want conf…
Asymptotic Normality of Generalized Low-Rank Matrix Sensing via Riemannian Geometry
Osbert Bastani
We prove an asymptotic normality guarantee for generalized low-rank matrix sensing -- i.e., matrix sensing under a general convex loss , where $M\…