791 citations · 2.5k across the 58 of their papers we have counts for
8 papers · 1 filter
On the admissibility of Horvitz-Thompson estimator for estimating causal effects under network interference
Vishesh Karwa, Edoardo M. Airoldi
The Horvitz-Thompson (H-T) estimator is widely used for estimating network causal effects. We study its optimality properties by embedding it in the class of all linear estimators.…
Wrapped Distributions on homogeneous Riemannian manifolds
Fernando Galaz-Garcia, Marios Papamichalis, Kathryn Turnbull +2
We provide a general framework for constructing probability distributions on Riemannian manifolds, taking advantage of area-preserving maps and isometries. Control over distributio…
Propensity score methodology in the presence of network entanglement between treatments
Panos Toulis, Alexander Volfovsky, Edoardo M. Airoldi
In experimental design and causal inference, it may happen that the treatment is not defined on individual experimental units, but rather on pairs or, more generally, on groups of…
The Proximal Robbins-Monro Method
Panos Toulis, Thibaut Horel, Edoardo M. Airoldi
The need for parameter estimation with massive datasets has reinvigorated interest in stochastic optimization and iterative estimation procedures. Stochastic approximations are at…
Sharp Total Variation Bounds for Finitely Exchangeable Arrays
Alexander Volfovsky, Edoardo Airoldi
In this article we demonstrate the relationship between finitely exchangeable arrays and finitely exchangeable sequences. We then derive sharp bounds on the total variation distanc…
Generalized Species Sampling Priors with Latent Beta reinforcements
Edoardo M. Airoldi, Thiago Costa, Federico Bassetti +2
Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appro…
Stochastic blockmodels with growing number of classes
David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi
We present asymptotic and finite-sample results on the use of stochastic blockmodels for the analysis of network data. We show that the fraction of misclassified network nodes conv…
Geometric Representations of Random Hypergraphs
Simón Lunagómez, Sayan Mukherjee, Robert L. Wolpert +1
A parametrization of hypergraphs based on the geometry of points in is developed. Informative prior distributions on hypergraphs are induced through this parametriza…