CSC 531 Project Details
As part of this course, every graduate student will complete a solo project with a significant theoretical component.
Types of projects
Below are suggestions for types of projects you could complete. The first set are research-oriented projects and are quite challenging (it is less common for students to pick these) which could involve:
- Making progress toward an open problem in learning theory; you don't necessarily have to solve the problem, but you have to show an honest effort;
- Posing a new, interesting problem and beginning to work on it;
- Showing connections between several problems or techniques;
- Developing a new, elegant understanding of a complicated result;
- A re-working of an existing, significant paper that significantly simplies the authors' analysis/solution.
The second set are survey-oriented (although presenting a single paper is also ok), such as:
- A synthesis of several related papers that distills the main ideas and presents them more simply and very concisely;
- Providing a new understanding/connections between several papers within some theme;
- Presenting a single learning theory paper to the class. Although this is listed last, for most students this is the most sensible option.
Initial meeting to green-light your project
In early March, I'll meet with each of you to ensure that you have a sensible project that is at the right scale. For ideas/themes for projects, take a look at the "Project ideas" section below.
Presentation
For each project, there will be a 20 to 30 minute presentation (depending on the time available) to discuss your findings, plus a few minutes for questions. These presentations will happen in the last week of lectures.
Submission
Each of you also will submit a 3-5 page report, not including
references. The maximum length is flexible depending on your project;
for instance, if you engage in an interesting research topic that
could lead to a paper, a longer writeup may be ideal.
For your report, please use the LaTeX style file and template below (this is just to get the geometry right, e.g. margins, font size, line spacing):
Your project writeups are due (via email) by Tuesday, April 15th, 11:59pm PDT. Please submit on time.
Project ideas
Below are some papers in various areas to help you think about project ideas; I may update these soon to include a few other areas.
Generalization
Deep learning and generalization
Algorithmic stability
Connection to cross-validation:
Compression schemes
Active learning
Transfer learning and lifelong learning
Fully online lifelong learning:
Lifelong learning of PAC learning tasks:
Learning under corruption
PAC-Bayesian bounds
Margin bounds:
Generalized PAC-Bayesian bounds:
PAC-Bayesian bounds with faster rates and unbounded losses:
Learning at faster rates
Massart and Tsybakov noise:
Efficient learning:
Online learning
Economics and Machine Learning
Private learnability as well as its connection to online learnability