72 citations · 231 across the 61 of their papers we have counts for
7 papers · 1 filter
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Optimal Transport and Conformal Prediction Sets
Richard A. Berk, Arun Kumar Kuchibhotla, Eric Tchetgen Tchetgen
In the United States and elsewhere, risk assessment algorithms are being used to help inform criminal justice decision-makers. A common intent is to forecast an offender's ``future…
Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework
Xu Shi, Kendrick Li, Wang Miao +2
Synthetic control (SC) methods are commonly used to estimate the treatment effect on a single treated unit in panel data settings. An SC is a weighted average of control units buil…
maars: Tidy Inference under the 'Models as Approximations' Framework in R
Riccardo Fogliato, Shamindra Shrotriya, Arun Kumar Kuchibhotla
Linear regression using ordinary least squares (OLS) is a critical part of every statistician's toolkit. In R, this is elegantly implemented via lm() and its related functions. How…
Median bias of M-estimators
Arun Kumar Kuchibhotla
In this note, we derive bounds on the median bias of univariate M-estimators under mild regularity conditions. These requirements are not sufficient to imply convergence in distrib…
The HulC: Confidence Regions from Convex Hulls
Arun Kumar Kuchibhotla, Sivaraman Balakrishnan, Larry Wasserman
We develop and analyze the HulC, an intuitive and general method for constructing confidence sets using the convex hull of estimates constructed from subsets of the data. Unlike cl…
Nested Conformal Prediction Sets for Classification with Applications to Probation Data
Arun K. Kuchibhotla, Richard A. Berk
Risk assessments to help inform criminal justice decisions have been used in the United States since the 1920s. Over the past several years, statistical learning risk algorithms ha…
Selection and Aggregation of Conformal Prediction Sets
Yachong Yang, Arun Kumar Kuchibhotla
Conformal prediction is a generic methodology for finite-sample valid distribution-free prediction. This technique has garnered a lot of attention in the literature partly because…