The course project is an opportunity for you to explore an interesting problem using a real-world dataset. You can either choose one of our suggested projects (TBD) or pick your own topic (the latter is encouraged). We encourage you to discuss your project with TAs/instructor to get feedback on your ideas.

Team: Projects can be done by a team of 2-4 students. You may use Piazza to find potential team mates.

Milestones: There are 3 deliverables:

• Proposal: A 1-page description of the project. Do not forget to include a title, the team members, and a short description of the problem, methodology, data, and evaluation metrics. Due on April 6.
• Midway report: Introduction, related work, details of the proposed method, and preliminary results if available (4-5 pages). Due on May 11.
• Final report: A full report written as a conference paper, including all the above in full detail, finished experiments and results, conclusion and future work (8 pages excluding references). Due on June 1.

All reports should be in NeurIPS format. There will be a class presentation, where you can present your work to the peers, instructors, and other community members who will stop by.

See here for possible topic ideas: https://andre-martins.github.io/pages/project-examples-for-deep-structured-learning-spring-2022.html