2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Efficient Parametric Approximations of Neural Network Function Space Distance
Nikita Dhawan, Sicong Huang, Juhan Bae +1
It is often useful to compactly summarize important properties of model parameters and training data so that they can be used later without storing and/or iterating over the entire…
cs.LG2022★ 2 cited
On the Difficulty of Defending Self-Supervised Learning against Model Extraction
Adam Dziedzic, Nikita Dhawan, Muhammad Ahmad Kaleem +2
Self-Supervised Learning (SSL) is an increasingly popular ML paradigm that trains models to transform complex inputs into representations without relying on explicit labels. These…