4 citations · 7 across the 5 of their papers we have counts for
18 papers
Multiclass versus Binary Differentially Private PAC Learning
Mark Bun, Marco Gaboardi, Satchit Sivakumar
We show a generic reduction from multiclass differentially private PAC learning to binary private PAC learning. We apply this transformation to a recently proposed binary private P…
Higher-order probabilistic adversarial computations: Categorical semantics and program logics
Alejandro Aguirre, Gilles Barthe, Marco Gaboardi +3
Adversarial computations are a widely studied class of computations where resource-bounded probabilistic adversaries have access to oracles, i.e., probabilistic procedures with pri…
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy
Di Wang, Marco Gaboardi, Adam Smith +1
In this paper, we study the Empirical Risk Minimization (ERM) problem in the non-interactive Local Differential Privacy (LDP) model. Previous research on this problem \citep{smith2…
Coupled Relational Symbolic Execution for Differential Privacy
Gian Pietro Farina, Stephen Chong, Marco Gaboardi
Differential privacy is a de facto standard in data privacy with applications in the private and public sectors. Most of the techniques that achieve differential privacy are based…
Graded Hoare Logic and its Categorical Semantics
Marco Gaboardi, Shin-ya Katsumata, Dominic Orchard +1
Deductive verification techniques based on program logics (i.e., the family of Floyd-Hoare logics) are a powerful approach for program reasoning. Recently, there has been a trend o…
The Complexity of Verifying Loop-Free Programs as Differentially Private
Marco Gaboardi, Kobbi Nissim, David Purser
We study the problem of verifying differential privacy for loop-free programs with probabilistic choice. Programs in this class can be seen as randomized Boolean circuits, which we…