534 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Zuse Institute BerlinDE7 papers
- Humboldt-Universität zu BerlinDE5 papers
- Technische Universität BerlinDE4 papers
- Freie Universität BerlinDE3 papers
- Max Planck Institute for Gravitational PhysicsDE3 papers
- Northern Illinois UniversityUS3 papers
- Eindhoven University of TechnologyNL2 papers
- Fraunhofer Institute for Open Communication SystemsDE2 papers
- Friedrich Schiller University JenaDE2 papers
- German Centre for Higher Education Research and Science StudiesDE2 papers
- Hasso Plattner InstituteDE2 papers
- Hochschule für Technik und Wirtschaft Dresden – University of Applied SciencesDE2 papers
6 papers · 1 filter
Sensitivity analysis of image classification models using generalized polynomial chaos
Lukas Bahr, Lucas Poßner, Konstantin Weise +2
Integrating advanced communication protocols in production has accelerated the adoption of data-driven predictive quality methods, notably machine learning (ML) models. However, ML…
Permutation Learning with Only N Parameters: From SoftSort to Self-Organizing Gaussians
Kai Uwe Barthel, Florian Barthel, Peter Eisert
Sorting and permutation learning are key concepts in optimization and machine learning, especially when organizing high-dimensional data into meaningful spatial layouts. The Gumbel…
FairGridSearch: A Framework to Compare Fairness-Enhancing Models
Shih-Chi Ma, Tatiana Ermakova, Benjamin Fabian
Machine learning models are increasingly used in critical decision-making applications. However, these models are susceptible to replicating or even amplifying bias present in real…
Learning to Schedule Heuristics in Branch-and-Bound
Antonia Chmiela, Elias B. Khalil, Ambros Gleixner +2
Primal heuristics play a crucial role in exact solvers for Mixed Integer Programming (MIP). While solvers are guaranteed to find optimal solutions given sufficient time, real-world…
Deep Metric Learning using Similarities from Nonlinear Rank Approximations
Konstantin Schall, Kai Uwe Barthel, Nico Hezel +1
In recent years, deep metric learning has achieved promising results in learning high dimensional semantic feature embeddings where the spatial relationships of the feature vectors…
Radial Prediction Layer
Christian Herta, Benjamin Voigt
For a broad variety of critical applications, it is essential to know how confident a classification prediction is. In this paper, we discuss the drawbacks of softmax to calculate…