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Saturday
, July 11
9:20am PDT
Introductory Remarks
JdF 1
9:30am PDT
Brian McFee, NYU, The Role of Structure Analysis in Music Discovery
JdF 1
10:30am PDT
Philippe Hamel, Google, To Have a Tiger by the Tail: Improving Music Recommendation for International Users
JdF 1
11:00am PDT
Arthur Flexer, Austrian Research Institute for Artificial Intelligence, The Impact of Hubness on Music Recommendation
JdF 1
11:30am PDT
Sander Dieleman, Ghent University, Deep Content-Based Music Recommendation
JdF 1
12:00pm PDT
Bob L. Sturm, Queen Mary University of London, The Scientific Evaluation of Music Content Analysis Systems: Valid Empirical Foundations for Future Real-World Impact
JdF 1
2:00pm PDT
Geoffroy Peeters, IRCAM, When Audio Features Reach Machine Learning
JdF 1
2:30pm PDT
Matthew Prockup, Drexel University, Pandora Media, Modeling Rhythmic Attributes in Music At Scale with Tree Ensembles and the Music Genome Project
JdF 1
2:50pm PDT
Dawen Liang, Columbia University, Content-Aware Collaborative Music Recommendation Using Pre-trained Neural Networks
JdF 1
3:10pm PDT
Thomas Wilmering, Queen Mary University of London, Towards High Level Feature Extraction from Large Live Music Recording Archives
JdF 1
4:30pm PDT
Cedric Mesnage, University of Bristol, Trend Extraction on Twitter Time Series for Music Discovery
JdF 1
4:50pm PDT
Keunwoo Choi, Queen Mary University of London, Understanding Music Playlists
JdF 1
5:10pm PDT
Bea Vad, University of Glasgow, Exploring Music with a Probabilistic Projection Interface
JdF 1
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ICML Workshops
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11, 2015
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