5 papers
Online activity prediction via generalized Indian buffet process models
Mario Beraha, Lorenzo Masoero, Stefano Favaro +1
Online A/B tests are the standard tool for data-driven decision-making at scale. Among the design choices with the largest impact on statistical power is the triggering mechanism:…
Confidence intervals for maximum unseen probabilities, with application to sequential sampling design
Alessandro Colombi, Mario Beraha, Amichai Painsky +1
Discovery problems often require deciding whether additional sampling is needed to detect all categories whose prevalence exceeds a prespecified threshold. We study this question u…
Conformal Inference for Open-Set and Imbalanced Classification
Tianmin Xie, Yanfei Zhou, Ziyi Liang +2
This paper presents a conformal prediction method for classification in highly imbalanced and open-set settings, where there are many possible classes and not all may be represente…
Large-scale entity resolution via microclustering Ewens--Pitman random partitions
Mario Beraha, Stefano Favaro
We introduce the microclustering Ewens--Pitman model for random partitions, obtained by scaling the strength parameter of the Ewens--Pitman model linearly with the sample size. The…
A smoothed-Bayesian approach to frequency recovery from sketched data
Mario Beraha, Stefano Favaro, Matteo Sesia
We provide a novel statistical perspective on a classical problem at the intersection of computer science and information theory: recovering the empirical frequency of a symbol in…