Project Report Grading Rubric

Students can work on projects individually,in pairs, or even in triplets. The grade will depend on the ideas, how well you present them in the report, how clearly you position your work relative to existing literature, how illuminating your experiments are, and well-supported your conclusions are.

You can use word or whatever you like to format your report, but ideally it will be in the format of a machine learning conference paper such as NIPS.

The idea is that this project report should be a manageable amount of work, but that if you want to turn your project into a paper, everything in the project report will need to be done anyways. If you feel that your project won't fit into this rubric, please talk to me. There are many ways to make contributions to a field!

Length: 4 to 8 pages, not including appendices. Don't be afraid to keep the text short and to the point, and to include large illustrative figures.

  1. Abstract (5 points) that summarizes the main idea of the project and its contributions.

  2. Introduction (5 points) that states the problem being addressed and why we might want to solve it.

  3. Figure or diagram (10 points) that shows the overall model or idea. The idea is to make your paper more accessible, especially to readers who are starting by skimming your paper.

  4. Formal description (20 points) of the model / loss function / conjecture / problem domain. Include at least one of:

  5. Related work (20 points) section and bibliography.

  6. Comparison or demonstration (20 points). Include at least one of:

  7. Limitations (15 points) of your approach.

  8. Conclusions (5 points)

Extra guidelines:

Positive examples: PixelVAE: A Latent Variable Model for Natural Images Your project report doesn't have to be as polished as this, of course!