Marius Köppel

According to our database, Marius Köppel authored at least 12 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Google Topics as a way out of the cookie dilemma?

Marius Köppel, Jan-Philipp Muttach, Gerrit Hornung

CoRR, 2024

10 Years of Fair Representations: Challenges and Opportunities.

Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer

CoRR, 2024

Can machine learning solve the challenge of adaptive learning and the individualization of learning paths? A field experiment in an online learning platform.

Tim Klausmann, Marius Köppel, Daniel Schunk, Isabell Zipperle

CoRR, 2024

2023

Google Topics als Ausweg aus dem Cookie-Dilemma? - Rechtliche Anforderungen an die technische Alternative zur individualisierten Werbung im Internet.

Jan-Philipp Muttach, Marius Köppel, Gerrit Hornung

Comput. und Recht, October, 2023

The Case for Correctability in Fair Machine Learning.

Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel

Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Invariant Representations with Stochastically Quantized Neural Networks.

Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Fair Interpretable Representation Learning with Correction Vectors.

Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer

CoRR, 2022

Fair Interpretable Learning via Correction Vectors.

Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer

CoRR, 2022

Fair Group-Shared Representations with Normalizing Flows.

Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer

CoRR, 2022

Ranking Creative Language Characteristics in Small Data Scenarios.

Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer

Proceedings of the 13th International Conference on Computational Creativity, Bozen-Bolzano, Italy, June 27, 2022

2020

Fair pairwise learning to rank.

Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019

Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance.

Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019