1.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Ludwig-Maximilians-Universität MünchenDE63 papers
- Technical University of MunichDE41 papers
- LMU KlinikumDE29 papers
- Imperial College LondonGB8 papers
- Helmholtz MunichDE6 papers
- TUM KlinikumDE6 papers
- Zimmer Biomet (Germany)DE6 papers
- Fraunhofer Institute for Integrated CircuitsDE4 papers
- Munich School of PhilosophyDE4 papers
- TU Dortmund UniversityDE4 papers
- University College LondonGB4 papers
- Zimmer Biomet (Netherlands)NL4 papers
14 papers · 1 filter
Mind the Gap: Measuring Generalization Performance Across Multiple Objectives
Matthias Feurer, Katharina Eggensperger, Edward Bergman +3
Modern machine learning models are often constructed taking into account multiple objectives, e.g., minimizing inference time while also maximizing accuracy. Multi-objective hyperp…
Mixture of Experts Distributional Regression: Implementation Using Robust Estimation with Adaptive First-order Methods
David Rügamer, Florian Pfisterer, Bernd Bischl +1
In this work, we propose an efficient implementation of mixtures of experts distributional regression models which exploits robust estimation by using stochastic first-order optimi…
Leveraging Memory Effects and Gradient Information in Consensus-Based Optimization: On Global Convergence in Mean-Field Law
Konstantin Riedl
In this paper we study consensus-based optimization (CBO), a versatile, flexible and customizable optimization method suitable for performing nonconvex and nonsmooth global optimiz…
An adaptive damped Newton method for strongly monotone and Lipschitz continuous operator equations
Pascal Heid
We will consider the damped Newton method for strongly monotone and Lipschitz continuous operator equations in a variational setting. We will provide a very accessible justificatio…
Improvement-Focused Causal Recourse (ICR)
Gunnar König, Timo Freiesleben, Moritz Grosse-Wentrup
Algorithmic recourse recommendations, such as Karimi et al.'s (2021) causal recourse (CR), inform stakeholders of how to act to revert unfavourable decisions. However, some actions…
The Virality of Hate Speech on Social Media
Abdurahman Maarouf, Nicolas Pröllochs, Stefan Feuerriegel
Online hate speech is responsible for violent attacks such as, e.g., the Pittsburgh synagogue shooting in 2018, thereby posing a significant threat to vulnerable groups and society…
Symbolic Recovery of Differential Equations: The Identifiability Problem
Philipp Scholl, Aras Bacho, Holger Boche +1
Symbolic recovery of differential equations is the ambitious attempt at automating the derivation of governing equations with the use of machine learning techniques. In contrast to…
Explaining the optimistic performance evaluation of newly proposed methods: a cross-design validation experiment
Christina Nießl, Sabine Hoffmann, Theresa Ullmann +1
The constant development of new data analysis methods in many fields of research is accompanied by an increasing awareness that these new methods often perform better in their intr…
Analyzing Social Media Activities at Bellingcat
Dominik Bär, Fausto Calderon, Michael Lawlor +3
Open-source journalism emerged as a new phenomenon in the media ecosystem, which uses crowdsourcing to fact-check and generate investigative reports for world events using open sou…
Locating disparities in machine learning
Moritz von Zahn, Oliver Hinz, Stefan Feuerriegel
Machine learning can provide predictions with disparate outcomes, in which subgroups of the population (e.g., defined by age, gender, or other sensitive attributes) are systematica…
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview
Florian Karl, Tobias Pielok, Julia Moosbauer +10
Hyperparameter optimization constitutes a large part of typical modern machine learning workflows. This arises from the fact that machine learning methods and corresponding preproc…
Experimental Standards for Deep Learning in Natural Language Processing Research
Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein +5
The field of Deep Learning (DL) has undergone explosive growth during the last decade, with a substantial impact on Natural Language Processing (NLP) as well. Yet, compared to more…
Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognition
Felix Ott, David Rügamer, Lucas Heublein +2
Cross-modal representation learning learns a shared embedding between two or more modalities to improve performance in a given task compared to using only one of the modalities. Cr…
On the Global Convergence of Particle Swarm Optimization Methods
Hui Huang, Jinniao Qiu, Konstantin Riedl
In this paper we provide a rigorous convergence analysis for the renowned particle swarm optimization method by using tools from stochastic calculus and the analysis of partial dif…