2 citations · 5 across the 11 of their papers we have counts for
5 papers · 1 filter
Optimal Compression of Locally Differentially Private Mechanisms
Abhin Shah, Wei-Ning Chen, Johannes Balle +2
Compressing the output of ε-locally differentially private (LDP) randomizers naively leads to suboptimal utility. In this work, we demonstrate the benefits of using schemes that jo…
A Computationally Efficient Method for Learning Exponential Family Distributions
Abhin Shah, Devavrat Shah, Gregory W. Wornell
We consider the question of learning the natural parameters of a parameter minimal exponential family from i.i.d. samples in a computationally and statistically efficient manne…
Selective Regression Under Fairness Criteria
Abhin Shah, Yuheng Bu, Joshua Ka-Wing Lee +4
Selective regression allows abstention from prediction if the confidence to make an accurate prediction is not sufficient. In general, by allowing a reject option, one expects the…
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge
Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja
Treatment effect estimation from observational data is a fundamental problem in causal inference. There are two very different schools of thought that have tackled this problem. On…
Treatment Effect Estimation using Invariant Risk Minimization
Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam +3
Inferring causal individual treatment effect (ITE) from observational data is a challenging problem whose difficulty is exacerbated by the presence of treatment assignment bias. In…