6 citations · 17 across the 14 of their papers we have counts for
4 papers · 1 filter
Learning bounded-degree polytrees with known skeleton
Davin Choo, Joy Qiping Yang, Arnab Bhattacharyya +1
We establish finite-sample guarantees for efficient proper learning of bounded-degree polytrees, a rich class of high-dimensional probability distributions and a subclass of Bayesi…
Tight Bounds for Machine Unlearning via Differential Privacy
Yiyang Huang, Clément L. Canonne
We consider the formulation of "machine unlearning" of Sekhari, Acharya, Kamath, and Suresh (NeurIPS 2021), which formalizes the so-called "right to be forgotten" by requiring that…
Private Distribution Learning with Public Data: The View from Sample Compression
Shai Ben-David, Alex Bie, Clément L. Canonne +2
We study the problem of private distribution learning with access to public data. In this setup, which we refer to as public-private learning, the learner is given public and priva…
Near-Optimal Degree Testing for Bayes Nets
Vipul Arora, Arnab Bhattacharyya, Clément L. Canonne +1
This paper considers the problem of testing the maximum in-degree of the Bayes net underlying an unknown probability distribution over , given sample access to .…