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 3; Deborah)

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

Update Fri Jan 23 11:49:35 CST 2009 -- we will be reading the Oliver and Hand paper.

Topic: Neural networks (February 12; Greg)

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

Update Wed Feb 4 12:11:20 CST 2009 -- we will be reading the Dietterich paper.

Topic: Learning theory (March 24; Lei)

Choose from one of the following 5 papers.

Update Tue Mar 17 17:44:27 CDT 2009 -- we will be reading the Balcan and Blum paper.

Topic: Instance-based learning (March 31; Vidhi)

Choose from one of the following 7 papers.

Update Thu Mar 19 11:19:54 CDT 2009 -- we will be reading the Quinlan paper.

Topic: Bayesian learning (April 7; Kevin)

Update Fri Feb 20 20:14:19 CST 2009 -- we will be reading the paper by Lowd and Domingos.

Topic: Support vector machines (April 14; Winston)

Update Thu Apr 9 15:35:00 CDT 2009 -- we will be reading the paper by Drucker, Wu, and Vapnik.

Choose from one of the following 6 papers.

Topic: Unsupervised learning (April 28)

Choose from one of the following 5 papers.

Topic: Boosting (April 30)

Choose from one of the following 4 papers.


Copyright © 2008 Greg Hamerly.
Computer Science Department
Baylor University

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