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most citedInformation bottleneck through variational glasses

23 citations · 36 across the 13 of their papers we have counts for

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Showing 2019Show all

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cs.CV2019★ 23 cited

Information bottleneck through variational glasses

Slava Voloshynovskiy, Mouad Kondah, Shideh Rezaeifar +3

Information bottleneck (IB) principle [1] has become an important element in information-theoretic analysis of deep models. Many state-of-the-art generative models of both Variatio…

cs.LG2019

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

Olga Taran, Shideh Rezaeifar, Taras Holotyak +1

In this paper, we address a problem of machine learning system vulnerability to adversarial attacks. We propose and investigate a Key based Diversified Aggregation (KDA) mechanism…

cs.LG2019

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…

cs.LG2019

Defending against adversarial attacks by randomized diversification

Olga Taran, Shideh Rezaeifar, Taras Holotyak +1

The vulnerability of machine learning systems to adversarial attacks questions their usage in many applications. In this paper, we propose a randomized diversification as a defense…

cs.LG2019

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…