23 citations · 28 across the 10 of their papers we have counts for
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cs.LG2026
Efficient and Optimal Learning of Discrete Distributions with Person-Level Privacy
Gautam Kamath, Mahbod Majid, Ankur Moitra +2
We study learning a discrete distribution under person-level differential privacy in the batched setting. Given users, each contributing i.i.d. samples from an unknown dist…
cs.LG2026
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
Eric Shen, Tony Wu, Mahbod Majid +1
We study the task of learning the structure of a -sparse Gaussian graphical model on variables from a single trajectory of Glauber dynamics. Beyond algorithmic consideration…
cs.LG2024
Sample-Efficient Private Learning of Mixtures of Gaussians
Hassan Ashtiani, Mahbod Majid, Shyam Narayanan
We study the problem of learning mixtures of Gaussians with approximate differential privacy. We prove that roughly samples suffice to learn a mix…