23 citations · 94 across the 24 of their papers we have counts for
5 papers · 1 filter
Optimal Robust Learning of Discrete Distributions from Batches
Ayush Jain, Alon Orlitsky
Many applications, including natural language processing, sensor networks, collaborative filtering, and federated learning, call for estimating discrete distributions from data col…
Unified Sample-Optimal Property Estimation in Near-Linear Time
Yi Hao, Alon Orlitsky
We consider the fundamental learning problem of estimating properties of distributions over large domains. Using a novel piecewise-polynomial approximation technique, we derive the…
The Broad Optimality of Profile Maximum Likelihood
Yi Hao, Alon Orlitsky
We study three fundamental statistical-learning problems: distribution estimation, property estimation, and property testing. We establish the profile maximum likelihood (PML) esti…
Data Amplification: A Unified and Competitive Approach to Property Estimation
Yi Hao, Alon Orlitsky, Ananda T. Suresh +1
Estimating properties of discrete distributions is a fundamental problem in statistical learning. We design the first unified, linear-time, competitive, property estimator that for…
Data Amplification: Instance-Optimal Property Estimation
Yi Hao, Alon Orlitsky
The best-known and most commonly used distribution-property estimation technique uses a plug-in estimator, with empirical frequency replacing the underlying distribution. We presen…