I am always excited to explore and try out new kinds of technologies. During my time studying at JKU, I have already learned many awesome things and am still eager to learn much more.
Associated with the Linz Institute of Technology and the Institute of Computational Perception @ JKU Linz , Austria
Christian Ganhör
Contact
Christian Ganhör
Student Research Assistant
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Johannes Kepler University Linz
Institute of Computational Perception
Altenberger Straße 69
Science Park 3, 403
A-4040 Linz, Austria - +43 732 2468 4712
- christian.ganhoer@jku.at
Publications
Peer-Reviewed Journal and Conference Papers
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
Proceedings of the 18th ACM Conference on Recommender Systems (RecSys), 2024
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation (BIAS @ SIGIR 2024), 2024
Emotion-aware Music Tower Blocks (EmoMTB): An Intelligent Audiovisual Interface for Music Discovery and Recommendation
International Journal of Multimedia Information Retrieval (IJMIR), 2023
Unlearning Protected User Attributes in Recommendations with Adversarial Training
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022
ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations
Proceedings of the 16th ACM Conference on Recommender Systems (RecSys), 2022
EmoMTB: Emotion-aware Music Tower Blocks
Proceedings of the 2022 ACM International Conference on Multimedia Retrieval (ICMR), 2022
Theses
Christian Ganhör
Single-Branch Network Architectures to Close the Modality Gap in Multimodal Recommendation
Johannes Kepler University Linz, Master's Thesis, 2024