213 citations · 491 across the 20 of their papers we have counts for
4 papers · 1 filter
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…
On generalization in moment-based domain adaptation
Werner Zellinger, Bernhard A Moser, Susanne Saminger-Platz
Domain adaptation algorithms are designed to minimize the misclassification risk of a discriminative model for a target domain with little training data by adapting a model from a…