6 citations · 15 across the 23 of their papers we have counts for
7 papers · 1 filter
Differentially Private Semantic Plans for Aggregate Insight Generation
Behrooz Razeghi
\texttt{URANIA} provides end-to-end differential privacy (DP) for summaries of data-dependent clusters. However, its cluster--keyword release does not directly provide collection-w…
Deep Privacy Funnel Model: From a Discriminative to a Generative Approach with an Application to Face Recognition
Behrooz Razeghi, Parsa Rahimi, Sébastien Marcel
In this study, we apply the information-theoretic Privacy Funnel (PF) model to face recognition and develop a method for privacy-preserving representation learning within an end-to…
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility
Behrooz Razeghi, Flavio P. Calmon, Deniz Gunduz +1
Bottleneck problems are an important class of optimization problems that have recently gained increasing attention in the domain of machine learning and information theory. They ar…
Variational Leakage: The Role of Information Complexity in Privacy Leakage
Amir Ahooye Atashin, Behrooz Razeghi, Deniz Gündüz +1
We study the role of information complexity in privacy leakage about an attribute of an adversary's interest, which is not known a priori to the system designer. Considering the su…
Reconstruction of Privacy-Sensitive Data from Protected Templates
Shideh Rezaeifar, Behrooz Razeghi, Olga Taran +2
In this paper, we address the problem of data reconstruction from privacy-protected templates, based on recent concept of sparse ternary coding with ambiguization (STCA). The STCA…
Clustering with Jointly Learned Nonlinear Transforms Over Discriminating Min-Max Similarity/Dissimilarity Assignment
Dimche Kostadinov, Behrooz Razeghi, Taras Holotyak +1
This paper presents a novel clustering concept that is based on jointly learned nonlinear transforms (NTs) with priors on the information loss and the discrimination. We introduce…