Markus Schedl

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Peter KneesFaculty of Informatics, TU WienVerified email at tuwien.ac.at
Gerhard WidmerProfessor of Computer Science, Johannes Kepler University LinzVerified email at jku.at
Marko TkalcicUniversity of PrimorskaVerified email at famnit.upr.si
Bruce FerwerdaAssociate Professor, Jönköping UniversityVerified email at ju.se
Yashar DeldjooTenure-Track Assistant Professor (RtD-b) of Computer Science, Polytechnic University of Bari, ItalyVerified email at acm.org
Bogdan IonescuPolitehnica University of BucharestVerified email at upb.ro
Andreu VallPumas-AIVerified email at pumas.ai
Christine BauerParis Lodron University SalzburgVerified email at plus.ac.at
Emilia GómezJoint Research Centre, European Commission and Music Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Julián UrbanoTU DelftVerified email at tudelft.nl
Sebastian BöckNXAIVerified email at nx-ai.com
Hamed ZamaniAssociate Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Ching-Wei ChenCrossing MindsVerified email at cwlabs.com
Marcin SkowronResearch Scientist | Austrian Research Institute for AI | Johannes Kepler UniversityVerified email at ofai.at
Cynthia C. S. LiemAssociate Professor, Multimedia Computing Group, Delft University of TechnologyVerified email at tudelft.nl
Mats SjöbergMachine learning specialist at CSCVerified email at csc.fi
Arthur FlexerJohannes Kepler University LinzVerified email at jku.at
Ionut MironicaAdobe ResearchVerified email at adobe.com

Markus Schedl

Professor at Johannes Kepler University Linz, Institute of Computational Perception

Verified email at jku.at - Homepage

Recommender Systems Information Retrieval Multimedia Human-centered AI Trustworthy AI


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Music recommender systems M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas Recommender systems handbook, 453-492, 2015	468*	2015
Current challenges and visions in music recommender systems research M Schedl, H Zamani, CW Chen, Y Deldjoo, M Elahi International Journal of Multimedia Information Retrieval 7, 95-116, 2018	395	2018
Music information retrieval: Recent developments and applications M Schedl, E Gómez, J Urbano Foundations and Trends® in Information Retrieval 8 (2-3), 127-261, 2014	370	2014
The LFM-1b Dataset for Music Retrieval and Recommendation M Schedl Proceedings of the 2016 ACM on international conference on multimedia …, 2016	236	2016
Recommender systems leveraging multimedia content Y Deldjoo, M Schedl, P Cremonesi, G Pasi ACM Computing Surveys (CSUR) 53 (5), 1-38, 2020	201	2020
Polyphonic piano note transcription with recurrent neural networks S Böck, M Schedl 2012 IEEE international conference on acoustics, speech and signal …, 2012	200	2012
A survey of music similarity and recommendation from music context data P Knees, M Schedl ACM Transactions on Multimedia Computing, Communications, and Applications …, 2013	197	2013
Fusing social media cues: personality prediction from twitter and instagram M Skowron, M Tkalčič, B Ferwerda, M Schedl Proceedings of the 25th international conference companion on world wide web …, 2016	189	2016
Evaluating the Online Capabilities of Onset Detection Methods S Böck, F Krebs, M Schedl ISMIR, 49-54, 2012	182	2012
The neglected user in music information retrieval research M Schedl, A Flexer, J Urbano Journal of Intelligent Information Systems 41 (3), 523-539, 2013	175	2013
The unfairness of popularity bias in music recommendation: A reproducibility study D Kowald, M Schedl, E Lex Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020	148	2020
Enhanced beat tracking with context-aware neural networks S Böck, M Schedl Proc. Int. Conf. Digital Audio Effects, 135-139, 2011	148	2011
An innovative three-dimensional user interface for exploring music collections enriched P Knees, M Schedl, T Pohle, G Widmer Proceedings of the 14th ACM international conference on Multimedia, 17-24, 2006	144	2006
A music search engine built upon audio-based and web-based similarity measures P Knees, T Pohle, M Schedl, G Widmer Proceedings of the 30th annual international ACM SIGIR conference on …, 2007	134	2007
Location-aware music recommendation using auto-tagging and hybrid matching M Kaminskas, F Ricci, M Schedl Proceedings of the 7th ACM Conference on Recommender Systems, 17-24, 2013	131	2013
Predicting personality traits with instagram pictures B Ferwerda, M Schedl, M Tkalcic Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015	128	2015
Recsys challenge 2018: Automatic music playlist continuation CW Chen, P Lamere, M Schedl, H Zamani Proceedings of the 12th ACM Conference on Recommender Systems, 527-528, 2018	125	2018
Local and global scaling reduce hubs in space. D Schnitzer, A Flexer, M Schedl, G Widmer Journal of Machine Learning Research 13 (10), 2012	125	2012
Investigating gender fairness of recommendation algorithms in the music domain AB Melchiorre, N Rekabsaz, E Parada-Cabaleiro, S Brandl, O Lesota, ... Information Processing & Management 58 (5), 102666, 2021	121	2021
Using instagram picture features to predict users’ personality B Ferwerda, M Schedl, M Tkalcic MultiMedia Modeling: 22nd International Conference, MMM 2016, Miami, FL, USA …, 2016	120	2016

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