8 citations · 19 across the 6 of their papers we have counts for
3 papers · 1 filter
A Blessing of Dimensionality in Membership Inference through Regularization
Jasper Tan, Daniel LeJeune, Blake Mason +2
Is overparameterization a privacy liability? In this work, we study the effect that the number of parameters has on a classifier's vulnerability to membership inference attacks. We…
MINER: Multiscale Implicit Neural Representations
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan +2
We introduce a new neural signal model designed for efficient high-resolution representation of large-scale signals. The key innovation in our multiscale implicit neural representa…
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
Jasper Tan, Blake Mason, Hamid Javadi +1
A surprising phenomenon in modern machine learning is the ability of a highly overparameterized model to generalize well (small error on the test data) even when it is trained to m…