Machine Learning for Music Discovery Workshop

International Conference on Machine Learning (ICML)

15 June 2019

Long Beach Convention Center, Long Beach, CA

Keynote Speaker

Yves Raimond, Director of Research/Engineering, Netflix

Invited Speakers

  • Kat Ellis, Amazon
  • Blair Kaneshiro, Stanford University
  • Brian McFee, New York University
  • Justin Salamon, Adobe Research
  • Zhengshan Shi, Stanford University

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:

  • Music recommendation and discovery
  • AI-based music creation and machine creativity
  • 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
  • Similarity metric learning
  • Learning to rank
  • Evaluation methodology
  • Deep learning applications for computational music research
  • Modeling hierarchical and long term music structures using deep learning
  • Cognitive models of music
  • Modeling ambiguity and preference in music
  • Software frameworks and tools for deep learning in music
  • Automatic classification of music (audio and MIDI)
  • Style-based interpreter recognition
  • Automatic composition and improvisation
  • Automatic score alignment
  • Polyphonic pitch detection
  • Chord extraction
  • Pattern discovery
  • Expressive performance modeling


Two page single-blind abstract submissions should be formatted according to the ICML template:

Note that you will need to modify the template to use the accepted version of the template for authors to appear.

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.

Submission Procedure

Papers should be submitted via EasyChair:

Poster Template

For posters we will follow the standard ICML requirements (24" x 36" in portrait orientation).


All questions about submissions should be emailed to Erik Schmidt ( or Oriol Nieto (

Important Dates

  • Abstracts Deadline: May 7, 2019
  • Notification of Acceptance: May 14, 2019
  • Camera-Ready Deadline: June 1, 2019
  • Workshop Date: June 15, 2019

Workshop Organizers

  • Erik M. Schmidt, Pandora
  • Oriol Nieto, Pandora
  • Katherine M. Kinnaird, Smith College
  • Fabien Gouyon, Pandora
  • Gert Lanckriet, Amazon