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
Christine BauerParis Lodron University SalzburgVerified email at plus.ac.at
Andreu VallPumas-AIVerified email at pumas.ai
Emilia GómezJoint Research Centre, European Commission and Music Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
Julián UrbanoTU DelftVerified email at tudelft.nl
Sebastian BöckenliteAIVerified email at enlite.ai
Cynthia C. S. LiemAssociate Professor, Multimedia Computing Group, Delft University of TechnologyVerified email at tudelft.nl
Hamed ZamaniAssistant Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Ching-Wei ChenCrossing MindsVerified email at cwlabs.com
Mats SjöbergMachine learning specialist at CSCVerified email at csc.fi
Arthur FlexerJohannes Kepler University LinzVerified email at jku.at
Marcin SkowronResearch Scientist | Austrian Research Institute for AI | Johannes Kepler UniversityVerified email at ofai.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	443*	2015
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	337	2014
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	336	2018
The LFM-1b Dataset for Music Retrieval and Recommendation M Schedl Proceedings of the 2016 ACM on international conference on multimedia …, 2016	207	2016
Polyphonic piano note transcription with recurrent neural networks S Böck, M Schedl 2012 IEEE international conference on acoustics, speech and signal …, 2012	189	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	186	2013
Evaluating the Online Capabilities of Onset Detection Methods S Böck, F Krebs, M Schedl ISMIR, 49-54, 2012	180	2012
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	176	2016
The neglected user in music information retrieval research M Schedl, A Flexer, J Urbano Journal of Intelligent Information Systems 41 (3), 523-539, 2013	173	2013
Recommender systems leveraging multimedia content Y Deldjoo, M Schedl, P Cremonesi, G Pasi ACM Computing Surveys (CSUR) 53 (5), 1-38, 2020	146	2020
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	139	2006
Enhanced beat tracking with context-aware neural networks S Böck, M Schedl Proc. Int. Conf. Digital Audio Effects, 135-139, 2011	138	2011
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	131	2007
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	129	2020
Predicting personality traits with instagram pictures B Ferwerda, M Schedl, M Tkalcic Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015	127	2015
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	124	2013
Local and global scaling reduce hubs in space. D Schnitzer, A Flexer, M Schedl, G Widmer Journal of Machine Learning Research 13 (10), 2012	123	2012
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	114	2016
On Rhythm and General Music Similarity. T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer ISMIR, 525-530, 2009	112	2009
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	102	2018

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