12 citations · 30 across the 8 of their papers we have counts for
3 papers · 1 filter
Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
Shlomi Hod, Lucas Rosenblatt, Julia Stoyanovich
Differentially private (DP) machine learning often relies on the availability of public data for tasks like privacy-utility trade-off estimation, hyperparameter tuning, and pretrai…
Quantifying Local Specialization in Deep Neural Networks
Shlomi Hod, Daniel Filan, Stephen Casper +2
A neural network is locally specialized to the extent that parts of its computational graph (i.e. structure) can be abstractly represented as performing some comprehensible sub-tas…
Performative Prediction in a Stateful World
Gavin Brown, Shlomi Hod, Iden Kalemaj
Deployed supervised machine learning models make predictions that interact with and influence the world. This phenomenon is called performative prediction by Perdomo et al. (ICML 2…