most citedParametric Feature Transfer: One-shot Federated Learning with Foundation Models

3 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

stat.ML2024

Distribution Learnability and Robustness

Shai Ben-David, Alex Bie, Gautam Kamath +1

We examine the relationship between learnability and robust (or agnostic) learnability for the problem of distribution learning. We show that, contrary to other learning settings (…

cs.LG2024★ 3 cited

Parametric Feature Transfer: One-shot Federated Learning with Foundation Models

Mahdi Beitollahi, Alex Bie, Sobhan Hemati +4

In one-shot federated learning (FL), clients collaboratively train a global model in a single round of communication. Existing approaches for one-shot FL enhance communication effi…

cs.LG2023

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…