Project Details

The final projects will be completed in groups of up to 4 students depending on class size. The project may consist of any combination of theoretical analysis, applications, and literature survey (possibly incorporating incorporate all three). The only constraint on the project is that it should include some aspect of probabilistic inference and/or learning. You should aim for a project suitable for submission to a machine learning conference e.g. NIPS, ICML, KDD, or domain-specific conferences e.g. CVPR, EMNLP, RECOMB.

Project Proposal

Proposals should be 1-2 pages long, and should include: * Project title and list of group members * Overview of project * Literature survey of 3 or more relevant papers * Description of data sets to use for the experiments, if applicable * Plan of activities, including final goal and how you plan to divide up the work

Final Project Report

The final project will be submitted through Relate in NIPS 2020 format i.e. main manuscript of up to 8 pages, plus unlimited pages of references. Any member of the group may submit the project.

You may include a supplement as additional pages appended to the main pdf. If you have supplements that cannot be submitted as pdf, please email a zipped file to me by the deadline. The main paper should be self-contained i.e. do not assume that the reviewer will read your supplement.

Project Presentation

Each group will give a short presentation of the course project in class. Live demonstrations of your software are highly encouraged (if applicable). Feedback from the presentation should be used to improve your project report.

You are expected to have a significant literature review and brainstorming stage. Your initial presentation may be primarily literature review, where the class helps you with brainstorming.

Finding references: A good place to start is using standard search with relevant keywords. From the initial search list, you should consider a breadth first search -- in future and past directions i.e., papers that cite the current paper, and papers that it cites. Once your idea is a bit more concrete, the course staff can also help supplement your reference list.

In-class presentations: Each group is expected to present to the class their findings. The midway project presentation will focus on background and literature review, and will primarily introduce the main ideas to the class. The presentation length is preferred to be in range 15-20 minutes.

Peer-grading: Presentations will be evaluated based on peer reports. Each individual must complete at least six peer reports each for literature review presentations as well as midterm presentations in order to receive the participation grade (10%).

Tentative Schedule

(We will have a 2-4 invited lectures, so may move presentations as appropriate.)


Students may develop projects based on their own research, with the constraint that it includes some aspect of probabilistic inference and/or learning. Alternatively, here are a list of possible directions.