David Penz

12 papers A* 1A 2B 2Journal 5Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A conf
Debiasing Implicit Feedback Recommenders via Sliced Wasserstein Distance-based Regularization.
RecSys
Gustavo Escobedo, David Penz, Markus Schedl
2025 — conf
Intermediate Languages Matter: Formal Languages and LLMs affect Neurosymbolic Reasoning.
SEMANTiCS (Posters, Demos, Workshops & Tutorials)
Alexander Beiser, Nysret Musliu, David Penz
2025 J jnl
Intermediate Languages Matter: Formal Languages and LLMs affect Neurosymbolic Reasoning.
CoRR
Alexander Beiser, David Penz, Nysret Musliu
2025 J jnl
Making LLMs Reason? The Intermediate Language Problem in Neurosymbolic Approaches.
CoRR
Alexander Beiser, David Penz
2025 J jnl
Maximally Expressive GNNs for Outerplanar Graphs.
Trans. Mach. Learn. Res.
Franka Bause, Fabian Jogl, Patrick Indri, Tamara Drucks, David Penz, Nils Morten Kriege, Thomas Gärtner, Pascal Welke, Maximilian Thiessen
2025 A conf
Mitigating Latent User Biases in Pre-trained VAE Recommendation Models via On-demand Input Space Transformation.
RecSys
David Penz, Gustavo Junior Escobedo Ticona, Markus Schedl
2023 J jnl
Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation.
Int. J. Multim. Inf. Retr.
Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl
2022 B conf
EmoMTB: Emotion-aware Music Tower Blocks.
ICMR
Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl
2022 B conf
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis.
CHIIR
Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz
2022 A* conf
Unlearning Protected User Attributes in Recommendations with Adversarial Training.
SIGIR
Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl
2022 J jnl
Unlearning Protected User Attributes in Recommendations with Adversarial Training.
CoRR
Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl
2021 — conf
Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features.
RecSys Challenge
Alexander Krauck, David Penz, Markus Schedl