6 citations · 10 across the 4 of their papers we have counts for
4 papers
Personalized Privacy Amplification via Importance Sampling
Dominik Fay, Sebastian Mair, Jens Sjölund
For scalable machine learning on large data sets, subsampling a representative subset is a common approach for efficient model training. This is often achieved through importance s…
Self-Supervised Siamese Autoencoders
Friederike Baier, Sebastian Mair, Samuel G. Fadel
In contrast to fully-supervised models, self-supervised representation learning only needs a fraction of data to be labeled and often achieves the same or even higher downstream pe…
Archetypal Analysis++: Rethinking the Initialization Strategy
Sebastian Mair, Jens Sjölund
Archetypal analysis is a matrix factorization method with convexity constraints. Due to local minima, a good initialization is essential, but frequently used initialization methods…
Principled Interpolation in Normalizing Flows
Samuel G. Fadel, Sebastian Mair, Ricardo da S. Torres +1
Generative models based on normalizing flows are very successful in modeling complex data distributions using simpler ones. However, straightforward linear interpolations show unex…