Search Results for author: Behrooz Razeghi

Found 9 papers, 2 papers with code

Variational Leakage: The Role of Information Complexity in Privacy Leakage

1 code implementation5 Jun 2021 Amir Ahooye Atashin, Behrooz Razeghi, Deniz Gündüz, Slava Voloshynovskiy

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.

Representation Learning

Privacy-Preserving Near Neighbor Search via Sparse Coding with Ambiguation

no code implementations8 Feb 2021 Behrooz Razeghi, Sohrab Ferdowsi, Dimche Kostadinov, Flavio. P. Calmon, Slava Voloshynovskiy

In this paper, we propose a framework for privacy-preserving approximate near neighbor search via stochastic sparsifying encoding.

Fairness

Privacy-Preserving Image Sharing via Sparsifying Layers on Convolutional Groups

1 code implementation4 Feb 2020 Sohrab Ferdowsi, Behrooz Razeghi, Taras Holotyak, Flavio P. Calmon, Slava Voloshynovskiy

We propose a practical framework to address the problem of privacy-aware image sharing in large-scale setups.

Single-Component Privacy Guarantees in Helper Data Systems and Sparse Coding with Ambiguation

no code implementations15 Jul 2019 Behrooz Razeghi, Taras Stanko, Boris Škorić, Slava Voloshynovskiy

We investigate the privacy of two approaches to (biometric) template protection: Helper Data Systems and Sparse Ternary Coding with Ambiguization.

Reconstruction of Privacy-Sensitive Data from Protected Templates

no code implementations8 May 2019 Shideh Rezaeifar, Behrooz Razeghi, Olga Taran, Taras Holotyak, Slava Voloshynovskiy

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).

Quantization

Network Learning with Local Propagation

no code implementations20 May 2018 Dimche Kostadinov, Behrooz Razeghi, Sohrab Ferdowsi, Slava Voloshynovskiy

This paper presents a locally decoupled network parameter learning with local propagation.

Privacy Preserving Identification Using Sparse Approximation with Ambiguization

no code implementations29 Sep 2017 Behrooz Razeghi, Slava Voloshynovskiy, Dimche Kostadinov, Olga Taran

The sparsifying transform and privacy amplification are not symmetric for the data owner and data user.

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