Slava Voloshynovskiy

research

∙ 12/14/2022

Mathematical model of printing-imaging channel for blind detection of fake copy detection patterns

Nowadays, copy detection patterns (CDP) appear as a very promising anti-...

0 Joakim Tutt, et al. ∙

research

∙ 10/28/2022

Digital twins of physical printing-imaging channel

In this paper, we address the problem of modeling a printing-imaging cha...

0 Yury Belousov, et al. ∙

research

∙ 10/11/2022

Printing variability of copy detection patterns

Copy detection pattern (CDP) is a novel solution for products' protectio...

0 Roman Chaban, et al. ∙

research

∙ 09/29/2022

Anomaly localization for copy detection patterns through print estimations

Copy detection patterns (CDP) are recent technologies for protecting pro...

1 Brian Pulfer, et al. ∙

research

∙ 07/11/2022

Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility

Bottleneck problems are an important class of optimization problems that...

31 Behrooz Razeghi, et al. ∙

research

∙ 06/23/2022

Authentication of Copy Detection Patterns under Machine Learning Attacks: A Supervised Approach

Copy detection patterns (CDP) are an attractive technology that allows m...

1 Brian Pulfer, et al. ∙

research

∙ 03/04/2022

Mobile authentication of copy detection patterns

In the recent years, the copy detection patterns (CDP) attracted a lot o...

0 Olga Taran, et al. ∙

research

∙ 12/15/2021

Funnels: Exact maximum likelihood with dimensionality reduction

Normalizing flows are diffeomorphic, typically dimension-preserving, mod...

0 Samuel Klein, et al. ∙

research

∙ 10/05/2021

Machine learning attack on copy detection patterns: are 1x1 patterns cloneable?

Nowadays, the modern economy critically requires reliable yet cheap prot...

0 Roman Chaban, et al. ∙

research

∙ 10/05/2021

Mobile authentication of copy detection patterns: how critical is to know fakes?

Protection of physical objects against counterfeiting is an important ta...

0 Olga Taran, et al. ∙

research

∙ 06/05/2021

Variational Leakage: The Role of Information Complexity in Privacy Leakage

We study the role of information complexity in privacy leakage about an ...

2 Amir Ahooye Atashin, et al. ∙

research

∙ 02/08/2021

Privacy-Preserving Near Neighbor Search via Sparse Coding with Ambiguation

In this paper, we propose a framework for privacy-preserving approximate...

0 Behrooz Razeghi, et al. ∙

research

∙ 09/09/2020

On Perfect Obfuscation: Local Information Geometry Analysis

We consider the problem of privacy-preserving data release for a specifi...

0 Behrooz Razeghi, et al. ∙

research

∙ 02/04/2020

Privacy-Preserving Image Sharing via Sparsifying Layers on Convolutional Groups

We propose a practical framework to address the problem of privacy-aware...

2 Sohrab Ferdowsi, et al. ∙

research

∙ 12/02/2019

Information bottleneck through variational glasses

Information bottleneck (IB) principle [1] has become an important elemen...

0 Slava Voloshynovskiy, et al. ∙

research

∙ 09/13/2019

ρ-VAE: Autoregressive parametrization of the VAE encoder

We make a minimal, but very effective alteration to the VAE model. This ...

0 Sohrab Ferdowsi, et al. ∙

research

∙ 07/15/2019

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

We investigate the privacy of two approaches to (biometric) template pro...

0 Behrooz Razeghi, et al. ∙

research

∙ 05/14/2019

Robustification of deep net classifiers by key based diversified aggregation with pre-filtering

In this paper, we address a problem of machine learning system vulnerabi...

0 Olga Taran, et al. ∙

research

∙ 05/08/2019

Reconstruction of Privacy-Sensitive Data from Protected Templates

In this paper, we address the problem of data reconstruction from privac...

0 Shideh Rezaeifar, et al. ∙

research

∙ 04/01/2019

Defending against adversarial attacks by randomized diversification

The vulnerability of machine learning systems to adversarial attacks que...

0 Olga Taran, et al. ∙

research

∙ 03/18/2019

Clonability of anti-counterfeiting printable graphical codes: a machine learning approach

In recent years, printable graphical codes have attracted a lot of atten...

0 Olga Taran, et al. ∙

research

∙ 01/31/2019

Network Parameter Learning Using Nonlinear Transforms, Local Representation Goals and Local Propagation Constraints

In this paper, we introduce a novel concept for learning of the paramete...

0 Dimche Kostadinov, et al. ∙

research

∙ 01/30/2019

Clustering with Jointly Learned Nonlinear Transforms Over Discriminating Min-Max Similarity/Dissimilarity Assignment

This paper presents a novel clustering concept that is based on jointly ...

0 Dimche Kostadinov, et al. ∙

research

∙ 12/10/2018

Aggregation and Embedding for Group Membership Verification

This paper proposes a group membership verification protocol preventing ...

0 Marzieh Gheisari, et al. ∙

research

∙ 09/10/2018

Classification by Re-generation: Towards Classification Based on Variational Inference

As Deep Neural Networks (DNNs) are considered the state-of-the-art in ma...

0 Shideh Rezaeifar, et al. ∙

research

∙ 09/05/2018

Bridging machine learning and cryptography in defence against adversarial attacks

In the last decade, deep learning algorithms have become very popular th...

0 Olga Taran, et al. ∙

research

∙ 06/07/2018

Privacy-Preserving Identification via Layered Sparse Code Design: Distributed Servers and Multiple Access Authorization

We propose a new computationally efficient privacy-preserving identifica...

0 Behrooz Razeghi, et al. ∙

research

∙ 05/20/2018

Network Learning with Local Propagation

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

0 Dimche Kostadinov, et al. ∙

research

∙ 10/31/2017

A multi-layer network based on Sparse Ternary Codes for universal vector compression

We present the multi-layer extension of the Sparse Ternary Codes (STC) f...

0 Sohrab Ferdowsi, et al. ∙

research

∙ 09/29/2017

Privacy Preserving Identification Using Sparse Approximation with Ambiguization

In this paper, we consider a privacy preserving encoding framework for i...

0 Behrooz Razeghi, et al. ∙

research

∙ 07/07/2017

A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising

A learning-based framework for representation of domain-specific images ...

0 Sohrab Ferdowsi, et al. ∙

research

∙ 01/26/2017

Sparse Ternary Codes for similarity search have higher coding gain than dense binary codes

This paper addresses the problem of Approximate Nearest Neighbor (ANN) s...

0 Sohrab Ferdowsi, et al. ∙

Slava Voloshynovskiy

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