Gerhard Widmer

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Markus SchedlProfessor at Johannes Kepler University Linz, Institute of Computational PerceptionVerified email at jku.at
Peter KneesFaculty of Informatics, TU WienVerified email at tuwien.ac.at
Elias PampalkNuance CommunicationsVerified email at nuance.com
Andreas ArztAppleVerified email at apple.com
Simon DixonCentre for Digital Music, Queen Mary University of LondonVerified email at qmul.ac.uk
Sebastian BöckenliteAIVerified email at enlite.ai
Maarten GrachtenIndependent Machine Learning ConsultantVerified email at grachten.eu
Werner GoeblProfessor, Head of Department of Music Acoustics, mdw – University of Music and Performing ArtsVerified email at mdw.ac.at
Arthur FlexerJohannes Kepler University LinzVerified email at jku.at
Filip KorzeniowskiMoises.AIVerified email at superfuzz.me
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Jan SchlüterJohannes Kepler University Linz (JKU)Verified email at jku.at
Fabien GouyonPandoraVerified email at pandora.com
Andreu VallPumas-AIVerified email at pumas.ai
Carlos Eduardo Cancino-ChacónJohannes Kepler University LinzVerified email at jku.at
Richard VoglFaculty of Informatics, TU WienVerified email at tuwien.ac.at
Harald FrostelDepartment for Computational Perception, Johannes Kepler University, Linz, AustriaVerified email at jku.at
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University MainzVerified email at informatik.uni-mainz.de
Xavier SerraDepartment of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), BarcelonaVerified email at upf.edu
Johannes FürnkranzJohannes Kepler University, LinzVerified email at faw.jku.at

Gerhard Widmer

Professor of Computer Science, Johannes Kepler University Linz

Verified email at jku.at - Homepage

Artificial Intelligence Machine Learning Sound and Music Computing Music Information Retrieval Computational Musicology


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Learning in the presence of concept drift and hidden contexts G Widmer, M Kubat Machine learning 23, 69-101, 1996	2310	1996
Incremental reduced error pruning J Fürnkranz, G Widmer Machine Learning Proceedings 1994, 70-77, 1994	564	1994
Improvements of Audio-Based Music Similarity and Genre Classificaton. E Pampalk, A Flexer, G Widmer ISMIR 5, 634-637, 2005	342	2005
Computational models of expressive music performance: The state of the art G Widmer, W Goebl Journal of new music research 33 (3), 203-216, 2004	302	2004
Effective learning in dynamic environments by explicit context tracking G Widmer, M Kubat Lecture Notes in Computer Science, 227-227, 1993	252	1993
Madmom: A new python audio and music signal processing library S Böck, F Korzeniowski, J Schlüter, F Krebs, G Widmer Proceedings of the 24th ACM international conference on Multimedia, 1174-1178, 2016	247	2016
MATCH: A Music Alignment Tool Chest. S Dixon, G Widmer ISMIR, 492-497, 2005	219	2005
Dynamic Playlist Generation Based on Skipping Behavior. E Pampalk, T Pohle, G Widmer ISMIR 5, 634-637, 2005	214	2005
Exploring music collections by browsing different views E Pampalk, S Dixon, G Widmer Computer Music Journal 28 (2), 49-62, 2004	209	2004
Towards Characterisation of Music via Rhythmic Patterns. S Dixon, F Gouyon, G Widmer ISMIR, 2004	199	2004
CP-JKU submissions for DCASE-2016: a hybrid approach using binaural i-vectors and deep convolutional neural networks H Eghbal-Zadeh, B Lehner, M Dorfer, G Widmer IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and …, 2016	198	2016
Evaluating rhythmic descriptors for musical genre classification F Gouyon, S Dixon, E Pampalk, G Widmer Proceedings of the AES 25th International Conference 196, 204, 2004	198	2004
Machine discoveries: A few simple, robust local expression principles G Widmer Journal of New Music Research 31 (1), 37-50, 2002	188	2002
Tracking context changes through meta-learning G Widmer Machine learning 27, 259-286, 1997	186	1997
Prediction of ordinal classes using regression trees S Kramer, G Widmer, B Pfahringer, M De Groeve Fundamenta Informaticae 47 (1-2), 1-13, 2001	182	2001
Prediction of ordinal classes using regression trees S Kramer, G Widmer, B Pfahringer, M De Groeve Fundamenta Informaticae 47 (1), 1-13, 2001	182	2001
In search of the Horowitz factor G Widmer, S Dixon, W Goebl, E Pampalk, A Tobudic AI Magazine 24 (3), 111-111, 2003	162	2003
Classification of dance music by periodicity patterns S Dixon, E Pampalk, G Widmer Johns Hopkins University, 2003	158	2003
Maximum filter vibrato suppression for onset detection S Böck, G Widmer Proc. of the 16th Int. Conf. on Digital Audio Effects (DAFx). Maynooth …, 2013	155	2013
Playlist Generation using Start and End Songs. A Flexer, D Schnitzer, M Gasser, G Widmer ISMIR 8, 173-178, 2008	154	2008

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