16 citations · 19 across the 8 of their papers we have counts for
4 papers · 1 filter
PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networks
Huzaifa Arif, Keerthiram Murugesan, Payel Das +2
This paper explores inference-time data leakage risks of deep neural networks (NNs), where a curious and honest model service provider is interested in retrieving users' private da…
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning
Deniz Koyuncu, Alex Gittens, Bülent Yener +1
Inference of causal structures from observational data is a key component of causal machine learning; in practice, this data may be incompletely observed. Prior work has demonstrat…
Reduced Label Complexity For Tight Regression
Alex Gittens, Malik Magdon-Ismail
Given data and labels the goal is find to minimize $\Vert{\rm X}\mathbf{w}-\mathbf{y}\V…
Simple Disentanglement of Style and Content in Visual Representations
Lilian Ngweta, Subha Maity, Alex Gittens +2
Learning visual representations with interpretable features, i.e., disentangled representations, remains a challenging problem. Existing methods demonstrate some success but are ha…