We invite proposals for short tutorials on machine learning and related fields. Ideally, the tutorial should attract a wide audience, provide a broad coverage of core research problems in its chosen research area, elucidate technical solutions, discuss their key insights, and stimulate future work. The tutorial should be broad enough to provide a basic introduction to the chosen area, but it should also be deep enough on the most important topics. Presentations that exclusively focus on the presenter's own work or commercial demonstrations are strongly discouraged.
Two kinds of proposals are particularly welcomed. Firstly, proposals from early-career researchers will be favorably reviewed. Secondly, joint tutorial-workshop proposals, which share the same topic with an ACML 2019 workshop proposal, are also highly encouraged.
A proposal should be 2 pages long, plus the presenters' biographies. The total duration of a tutorial should be approximately 2.5 hours (including time for breaks).
A tutorial proposal should contain the following:
- Title and abstract suitable for web publicity
- Overview describing the topic
- Relevance and significance of the topic for the machine learning community
- Research areas and prior knowledge required of potential audience
- A brief outline of the tutorial structure showing that the tutorial's core content can be covered in 2.5 hours.
- Distribution of work in the case of multiple presenters
- Samples of relevant past tutorials and teaching materials
- Description of presentation medium (slides, multimedia, demos, etc.) and technical equipment (e.g., internet access)
- A brief academic bio for each proposed presenter, including name, email, webpage, research expertise, and list of publications in tutorial area.
- Jul.20, 2019: Tutorial proposals due
- Aug.04, 2019: Acceptance notification
- Oct.20, 2019: Tutorial material/Website due
- Nov.17, 2019: ACML tutorials