From the syllabus:

You will summarize your project results in a written report and an oral presentation. If your project involves an implementation, then you may be asked to also give a brief demonstration. The written report must use a professional writing style similar to that found in an ACM or IEEE journal, including abstract, introduction, summary of related work, your contribution, references, and an appendix (if necessary). The oral presentation will be to the entire class at the end of the semester: during Dead Week (December 8-12), and if necessary, during the week prior to Dead Week (December 1-5). You will submit your written report to me no later than 11:59:59 p.m. on December 14 (the last day of dead week). In accordance with UNL dead week policies, you have now been informed in writing of the nature and scope of this project prior to the eighth week of classes.

Later this semester (around October 6) I will set a deadline for submission of 1-3 paragraph proposals on your projects. You must do this in order to get full credit for your project, and you must get my approval on it before starting work on your project. I will provide a list of possible topics later this semester, but you may propose your own topic as well. To be a valid topic, it must go beyond the scope of the course. So your project could be on a topic we did not cover in class at all, or could more deeply explore a topic we covered in class.

• Rules on projects, a.k.a. what to turn in for your proposal and for your final project writeup

• Tips on Presenting Technical Material

• Schedule of this semester's project presentations

• Sources of project ideas:
  • If your thesis research or a project you are doing for another course is appropriate for this course's project, I may allow you to use it for this course. But you still need to submit a proposal.
  • See this list of ideas for topic surveys or implementations of existing systems. Some of these could be turned into research projects, e.g. a thesis or project for MS or BS.
  • Check the projects done in the following previous offerings of CSCE 970 (Pattern Recognition) and CSCE 478/878 (Machine Learning). You may choose to expand on one of these projects.
    • CSCE 970, Spring 1999
    • CSCE 970, Spring 2001
    • CSCE 970, Spring 2003
    • CSCE 478/878, Fall 1999
    • CSCE 478/878, Fall 2001
  • Look at projects done in other machine learning courses. But if you choose such a project, please do not contact the instructors or TAs of these courses without talking to me first! If you think one of these ideas is interesting, send me a proposal just like you would with any other project idea. Then, if necessary, I will contact the instructor of that course for more information.
  • Look at the "Summary and Further Reading" sections at the end of each chapter of the textbook.
  • Review papers from recent conference proceedings and journals. (see my machine learning hotlist for some links).
  • See this survey paper by Tom Dietterich on current research directions in machine learning [from AI Magazine, vol. 18, no. 4, pp. 97-136].

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Last modified 16 August 2011; please report problems to sscott AT cse.