The 2018 Joint Workshop on Machine Learning for Music
The Federated Artificial Intelligence Meeting (FAIM)
A joint workshop program of ICML, IJCAI/ECAI, and AAMAS
Stockholm, Sweden
Saturday, July 14th, 2018
 A Joint Meeting of the:
Machine Learning for Music Discovery Workshop (ICML)
Erik M. Schmidt, Oriol Nieto, Katherine M. Kinnaird, Fabien Gouyon, Gert Lanckriet
MML 2018: 11th International Workshop on Machine Learning and Music (ICML)
Rafael Ramirez Melendez, José M. Iñesta, Darrell Conklin
Keynote Speaker:
Invited Speakers:
Call for Papers
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. Further, the whole music ecosystem --from creation to consumption-- is being disrupted to its core by current developments in machine learning, and in particular recent advances in deep learning. The topics discussed in the workshop will span a variety of music generation and recommender systems challenges including cross-cultural recommendation, content-based audio processing and representation learning, automatic music tagging, synthesis, style-transfer, and evaluation.
We invite the research community, from both industry and academia, to submit 2-page extended abstracts on topics such as:
Abstracts should be formatted according to the ICML template:
Only papers using the above template will be considered. Word templates will not be provided. Review is single-blind. A third page may be used for references only.
Papers should be submitted via email to the following address:
Accepted papers will be published online.
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