no code implementations • ICML 2017 • Sebastian Mair, Ahcène Boubekki, Ulf Brefeld
Archetypal Analysis is the method of choice to compute interpretable matrix factorizations.
1 code implementation • NeurIPS 2019 • Sebastian Mair, Ulf Brefeld
Archetypal analysis represents instances as linear mixtures of prototypes (the archetypes) that lie on the boundary of the convex hull of the data.
no code implementations • 22 Oct 2020 • Samuel G. Fadel, Sebastian Mair, Ricardo da S. Torres, Ulf Brefeld
In this paper, we solve this issue by enforcing a fixed norm and, hence, change the base distribution, to allow for a principled way of interpolation.
no code implementations • 31 Jan 2023 • Sebastian Mair, Jens Sjölund
Archetypal analysis is a matrix factorization method with convexity constraints.
no code implementations • 5 Apr 2023 • Friederike Baier, Sebastian Mair, Samuel G. Fadel
In this paper, we present a new self-supervised method that combines the benefits of Siamese architectures and denoising autoencoders.
no code implementations • 27 May 2023 • Di Liu, Sebastian Mair, Kang Yang, Simone Baldi, Paolo Frasca, Matthias Althoff
We show that self-organization promotes resilience to acceleration limits and communication failures, i. e., homogenizing to a common group behavior makes the platoon recover from these causes of impairments.
no code implementations • 5 Jul 2023 • Dominik Fay, Sebastian Mair, Jens Sjölund
We first consider the general case where an arbitrary personalized differentially private mechanism is subsampled with an arbitrary importance sampling distribution and show that the resulting mechanism also satisfies personalized differential privacy.
1 code implementation • 30 Oct 2023 • Zheng Zhao, Sebastian Mair, Thomas B. Schön, Jens Sjölund
Recently, partial Bayesian neural networks (pBNNs), which only consider a subset of the parameters to be stochastic, were shown to perform competitively with full Bayesian neural networks.
no code implementations • 13 Dec 2023 • Sebastian Mair, Matthias Althoff
Cooperative Adaptive Cruise Control (CACC) is a well-studied technology for forming string-stable vehicle platoons.
no code implementations • 15 Feb 2024 • Maria Bånkestad, Jennifer Andersson, Sebastian Mair, Jens Sjölund
Typically, the reduction approaches either remove edges (sparsification) or merge nodes (coarsening) in an unsupervised way with no specific downstream task in mind.