7 citations · 11 across the 3 of their papers we have counts for
4 papers
On Data Augmentation and Adversarial Risk: An Empirical Analysis
Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus +5
Data augmentation techniques have become standard practice in deep learning, as it has been shown to greatly improve the generalisation abilities of models. These techniques rely o…
ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy
Natalia Shepeleva, Werner Zellinger, Michal Lewandowski +1
We propose a new metric space of ReLU activation codes equipped with a truncated Hamming distance which establishes an isometry between its elements and polyhedral bodies in the in…
Moment-Based Domain Adaptation: Learning Bounds and Algorithms
Werner Zellinger
This thesis contributes to the mathematical foundation of domain adaptation as emerging field in machine learning. In contrast to classical statistical learning, the framework of d…
Mixture Density Generative Adversarial Networks
Hamid Eghbal-zadeh, Werner Zellinger, Gerhard Widmer
Generative Adversarial Networks have surprising ability for generating sharp and realistic images, though they are known to suffer from the so-called mode collapse problem. In this…