Marius Köppel

20 papers A* 1B 1C 1Journal 12Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance. Mach. Learn. Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer
2025	—	`conf`	Stochastic Fairness Interventions Are Arbitrary. EWAF Mattia Cerrato, Marius Köppel, Kiara Stempel, Philipp Wolf, Stefan Kramer
2024	J	`jnl`	10 Years of Fair Representations: Challenges and Opportunities. CoRR Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer
2024	J	`jnl`	Can machine learning solve the challenge of adaptive learning and the individualization of learning paths? A field experiment in an online learning platform. CoRR Tim Klausmann, Marius Köppel, Daniel Schunk, Isabell Zipperle
2024	J	`jnl`	Google Topics as a way out of the cookie dilemma? CoRR Marius Köppel, Jan-Philipp Muttach, Gerrit Hornung
2024	J	`jnl`	Predicting NOx emissions in Biochar Production Plants using Machine Learning. CoRR Marius Köppel, Niklas Witzig, Tim Klausmann, Mattia Cerrato, Tobias Schweitzer, Jochen Weber, Erdem Yilmaz, Juan Chimbo, Bernardo del Campo, Lissete Davila, David Barreno
2024	—	`conf`	Trust in Fair Algorithms: Pilot Experiment. EWAF Mattia Cerrato, Marius Köppel, Kiara Stempel, Alesia Vallenas Coronel, Niklas Witzig
2023	J	`jnl`	Google Topics als Ausweg aus dem Cookie-Dilemma? - Rechtliche Anforderungen an die technische Alternative zur individualisierten Werbung im Internet. Comput. und Recht Jan-Philipp Muttach, Marius Köppel, Gerrit Hornung
2023	—	`conf`	Google Topics as a Way Out of the Cookie Dilemma? PKDD/ECML Workshops (1) Marius Köppel, Jan-Philipp Muttach, Gerrit Hornung
2023	A*	`conf`	Invariant Representations with Stochastically Quantized Neural Networks. AAAI Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
2023	—	`conf`	The Case for Correctability in Fair Machine Learning. EWAF Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel
2022	J	`jnl`	Fair Group-Shared Representations with Normalizing Flows. CoRR Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
2022	J	`jnl`	Fair Interpretable Learning via Correction Vectors. CoRR Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
2022	J	`jnl`	Fair Interpretable Representation Learning with Correction Vectors. CoRR Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
2022	J	`jnl`	Invariant Representations with Stochastically Quantized Neural Networks. CoRR Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
2022	C	`conf`	Ranking Creative Language Characteristics in Small Data Scenarios. ICCC Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer
2020	B	`conf`	Fair pairwise learning to rank. DSAA Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
2020	J	`jnl`	Ranking Creative Language Characteristics in Small Data Scenarios. CoRR Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer
2019	—	`conf`	Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. ECML/PKDD (3) Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer
2019	J	`jnl`	Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. CoRR Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer