most citedInformation bottleneck through variational glasses

23 citations · 23 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV201923 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

-VAE: Autoregressive parametrization of the VAE encoder

Sohrab Ferdowsi, Maurits Diephuis, Shideh Rezaeifar +1

We make a minimal, but very effective alteration to the VAE model. This is about a drop-in replacement for the (sample-dependent) approximate posterior to change it from the standa…

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…