CSI 5325 paper presentations

Here we will organize the papers that the students in the class will present. Typically, we will have a presentation on one paper relevant to the topic of discussion shortly after the professor has finished his lectures on the topic.

I will put up a list of potential papers for each topic; it's up to the presenter to choose the paper at least a week prior to the presentation. Let me know which paper you choose. Note that some papers are in postscript format -- you may need to get a postscript reader for these.

Before the presentation, everyone in the class must read the paper so we may have a fruitful discussion. Thus the target audience of the presentation is people who already have learned something about the topic.

Guidelines and evaluation

The presentation should use slides and be about 20 minutes long, and allow for an additional 10 minutes of discussion (either at the end, or during the talk). As a rule of thumb, 1 minute of presentation means about 1 slide. The presentation should address and lead the class in a discussion of the main points of the article. In particular, talk about:

The focus of the presentation should be on presenting the work, but do spend a little time giving your critique of the work as appropriate.

Consider this advice from Charles Elkan on notes on giving a research talk

Your grade will be based on the clarity and quality of your presentation, how well you lead the discussion and are able to answer any questions that come up.

Topic: Decision trees (February 4; Brandy)

Choose from one of the following 5 papers. I recommend the Oliver or Blockeel papers.

Update (Tue Jan 29 12:17:36 CST 2008) -- we will be reading the paper by Kohavi and Kunz.

Topic: Neural networks (February 14; Peter)

Choose from one of the following 7 papers. I recommend the Caruana or Dietterich papers.

Update (Thu Feb 7 13:10:38 CST 2008) -- we will be reading the paper by Caruana, Lawrence, and Giles.

Topic: Evaluating hypotheses (February 21; no one)

We'll skip the paper presentation for this topic.

Topic: Learning theory (March 25; Ben)

Choose from one of the following 5 papers.

Update (Tue Mar 18 12:31:57 CDT 2008) -- we will be reading the Valiant paper.

Topic: Instance-based learning (April 1; Nate)

Choose from one of the following 7 papers.

Update (Wed Mar 26 20:47:52 CDT 2008) -- we will be reading the Arya paper.

Topic: Support vector machines (April 15; Aaron)

Choose from one of the following 6 papers.

Update (Mon Apr 7 23:00:44 CDT 2008) -- we will be reading the Drucker paper.

Topic: Unsupervised learning (April 29; Alex)

Choose from one of the following 5 papers.

Update (Sun Apr 20 06:19:46 CDT 2008) -- we will be reading the Ng paper.

Topic: Boosting (May 1; Chris)

Choose from one of the following 4 papers.

Update (Sun Apr 27 21:02:20 CDT 2008) -- we will be reading the Hao paper.


Copyright © 2008 Greg Hamerly.
Computer Science Department
Baylor University

valid html and css