| Date: | May 2, 2007 |
| Time: | 12:00 PM - 1:00 PM (Pizza (While it lasts)) |
| Location: | 3305 Newell-Simon Hall |
| Speaker: | Andrew Arnold Ph.D. Candidate |
| Title: | A Comparison of Methods for Transductive Transfer Learning |
| Abstract: |
We examine the problem of domain adaptation for protein name
extraction. First we define the general problem of transfer learning
and the particular sub-problem of domain adaptation. We then describe
some current state of the art supervised and transductive approaches
involving support vector machines and maximum entropy models. Using
these as inspiration, we turn to the unsupervised version of the
problem and introduce a novel maximum entropy based technique that
achieves comparable performance with no labeled target data. We
present the results of experimental comparisons between all the
methods described and conclude with a discussion of trends observed
and promising routes for future work. |