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 FerwerdaAssistant 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
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Emilia GómezJoint Research Centre, European Commission and Music Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Christine BauerUtrecht UniversityVerified email at uu.nl
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
Hamid Eghbal-zadehMetaVerified email at meta.com
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
Mats SjöbergMachine learning specialist at CSCVerified email at csc.fi
Hamed ZamaniAssistant Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Ching-Wei ChenSpotifyVerified email at cwlabs.com
Arthur FlexerJohannes Kepler University LinzVerified email at jku.at
Marcin SkowronResearch Scientist | Austrian Research Institute for AI | Johannes Kepler UniversityVerified email at ofai.at

Markus Schedl

Professor at Johannes Kepler University Linz, Institute of Computational Perception

Verified email at jku.at - Homepage

Recommender Systems Information Retrieval Multimedia Fairness Human-centered AI


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Music recommender systems M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas Recommender systems handbook, 453-492, 2015	393*	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	290	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	267	2018
Polyphonic piano note transcription with recurrent neural networks S Böck, M Schedl 2012 IEEE international conference on acoustics, speech and signal …, 2012	182	2012
The LFM-1b Dataset for Music Retrieval and Recommendation M Schedl Proceedings of the 2016 ACM on international conference on multimedia …, 2016	180	2016
Evaluating the Online Capabilities of Onset Detection Methods S Böck, F Krebs, M Schedl ISMIR, 49-54, 2012	165	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	161	2013
The neglected user in music information retrieval research M Schedl, A Flexer, J Urbano Journal of Intelligent Information Systems 41 (3), 523-539, 2013	161	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	152	2016
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	137	2006
Enhanced beat tracking with context-aware neural networks S Böck, M Schedl Proc. Int. Conf. Digital Audio Effects, 135-139, 2011	132	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	130	2007
Predicting personality traits with instagram pictures B Ferwerda, M Schedl, M Tkalcic Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015	118	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	117	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	114	2012
On Rhythm and General Music Similarity. T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer ISMIR, 525-530, 2009	108	2009
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	99	2016
Using block-level features for genre classification, tag classification and music similarity estimation K Seyerlehner, M Schedl, T Pohle, P Knees Submission to Audio Music Similarity and Retrieval Task of MIREX 2010 (2), 3, 2010	97	2010
The MediaEval 2015 Affective Impact of Movies Task. M Sjöberg, Y Baveye, H Wang, VL Quang, B Ionescu, E Dellandréa, ... MediaEval 1436, 2015	94	2015
The million musical tweet dataset: what we can learn from microblogs D Hauger, M Schedl, A Košir, M Tkalčič Proceedings of the 14th Conference of the International Society for Music …, 2013	92	2013

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