ML4MD 2015 - Workshop on Machine Learning for Music Discovery

=== ICML Workshop: Machine Learning for Music Discovery ===
International Conference on Machine Learning (ICML) 2015
Lille, France
July 11th, 2015
https://sites.google.com/site/ml4md2015/
The ever-increasing size and accessibility of vast music libraries has created a demand more than ever for machine learning systems that are capable of understanding and organizing this complex data. Collaborative filtering provides excellent music recommendations when the necessary user data is available, but suffers heavily from the cold-start problem. Furthermore, defining musical similarity directly is challenging as a myriad of features plays a role (e.g., cultural, emotional, timbral, rhythmic). The topics discussed will span a variety of challenges faced by music recommender systems, including cross-cultural recommendation, content-based audio processing and representation learning, automatic music tagging, and evaluation.
We invite 2-page extended abstracts, from both industry and academia, addressing any of the following topics:
* Music recommendation and discovery
* Content-based and multimodal music recommender systems
* Transfer learning and semi-supervised learning for music discovery
* Audio and semantic content-based machine learning (e.g., genre, mood, style, rhythm)
* Browsing and visualization of large music and listener datasets
* Metric learning
* Learning to rank
* Evaluation methodologies
Abstracts should be formatted according to the ICML template (http://icml.cc/2015/wp-content/uploads/2014/12/icm...). Word templates will not be provided.
Papers should be submitted via email to the following address: machine-learning-for-music-discovery-AT-googlegroups.com
Accepted papers will be published online.
=== Important Dates ===
*** Abstracts Deadline: May 1, 2015
*** Notification of Acceptance: May 10, 2015
=== Invited Speakers ===
Brian McFee, NYU Center for Data Science
Philippe Hamel, Google
Sander Dieleman, Ghent University
Arthur Flexer, Austrian Research Institute for Artificial Intelligence
Geoffroy Peeters, IRCAM
Bob L. Sturm, School of Electronic Engineering and Computer Science, C4DM, Queen Mary University
=== Workshop Organizers ===
Erik Schmidt, Pandora
Fabien Gouyon, Pandora
Gert Lanckriet, University of California San Diego