ICML 2021 Call for Tutorials
The ICML 2021 Organizing Committee invites proposals for tutorials to be given on July 19th, 2021, immediately preceding the main conference.
We welcome proposals for tutorials on either core machine learning topics or topics of emerging importance for machine learning. We will consider tutorials on any topic if the proposal makes a strong argument that such a tutorial serves an important function for the ICML community. Tutorials should be of interest to a substantial part of the ICML audience and represent a sufficiently mature area of research or practice.
We anticipate to accept ten tutorials, each tutorial will be two hours long.
Proposals should be structured to answer the following questions:
- Title
- Brief description and outline: What will the tutorial be about? Please provide an outline of what you plan to cover, including references and details on how much time you will spend on each topic. We encourage the presenters to demonstrate coverage and representativeness of the chosen area of research, not to focus solely on their own results or tools.
- Goals: What objectives does the tutorial serve? Why is it important to include it as a part of ICML 2021?
- Target audience: Who is your target audience? How many participants do you expect to see? What kind of background do you expect them to have?
Please include the names and email addresses of the presenters, along with brief bios and the description of each presenter’s expertise in the tutorial area. We suggest that each tutorial is given by at most two presenters. If there is more than one presenter, please describe how time will be split.
If available, please include samples of your past tutorial (or other relevant) slides or links to video recordings on the topic.
Tutorial proposals should be submitted to tutorials@icml.cc by The date TutorialSubmissionDeadline not found.. Acceptance and rejection decisions will be announced on The date TutorialAnnouncements not found..
Tutorial Chairs, ICML 2021
Caroline Uhler and Quoc Le
ICML