213 citations · 320 across the 6 of their papers we have counts for
6 papers
Markov Chain Gradient Descent in Hilbert Spaces
Priyanka Roy, Susanne Saminger-Platz
In this paper, we study a Markov chain-based stochastic gradient algorithm in general Hilbert spaces, aiming at approximating the optimal solution of a quadratic loss function. We…
Coherence and avoidance of sure loss for standardized functions and semicopulas
Erich Peter Klement, Damjana Kokol Bukovšek, Blaž Mojškerc +3
We discuss avoidance of sure loss and coherence results for semicopulas and standardized functions, i.e., for grounded, 1-increasing functions with value at .…
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…
Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment
Werner Zellinger, Bernhard A. Moser, Thomas Grubinger +3
A novel approach for unsupervised domain adaptation for neural networks is proposed. It relies on metric-based regularization of the learning process. The metric-based regularizati…
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning
Werner Zellinger, Thomas Grubinger, Edwin Lughofer +2
The learning of domain-invariant representations in the context of domain adaptation with neural networks is considered. We propose a new regularization method that minimizes the d…
Dominance in the family of Sugeno-Weber t-norms
Manuel Kauers, Veronika Pillwein, Susanne Saminger-Platz
The dominance relationship between two members of the family of Sugeno Weber t-norms is proven by using a quantifer elimination algorithm. Further it is shown that dominance is a t…