The Noisy-SGD algorithm is widely used for privately training machine
le...
The information bottleneck (IB) method aims to find compressed
represent...
We investigate the contraction properties of locally differentially priv...
We introduce a new differential privacy (DP) accountant called the
saddl...
Most differential privacy mechanisms are applied (i.e., composed) numero...
We consider the problem of producing fair probabilistic classifiers for
...
We investigate the local differential privacy (LDP) guarantees of a
rand...
We propose an information-theoretic technique for analyzing privacy
guar...
Information bottleneck (IB) and privacy funnel (PF) are two closely rela...
We consider three different variants of differential privacy (DP), namel...
In this paper, we consider the problem of responding to a count query (o...
We investigate the framework of privacy amplification by iteration, rece...
We derive the optimal differential privacy (DP) parameters of a mechanis...
Identifying features that leak information about sensitive attributes is...
Inspired by recent interests of developing machine learning and data min...
We investigate the problem of reliable communication between two legitim...
We introduce a novel definition of curvature for hypergraphs, a natural
...
Given a pair of random variables (X,Y)∼ P_XY and two convex functions
f_...
In a survey disclosure model, we consider an additive noise privacy mech...
A privacy-constrained information extraction problem is considered where...