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8/27/07 2:30pm

Introductory meeting

9/3/07 2:30pm

Labor day

9/10/07 2:30pm

(Arthur) prinicpled stream weight tuning for factored observation models

9/17/07 2:30pm

Bryce Hant & Alwan. A psychoacoustic-masking model to predict the perceptionof speech-like stimuli in noise. Speech Communication 40 (2003) 291–313

9/25/07 1:00pm

(Harsh) Tracking in Video using a Time Series Transformation Learning approach

Hello everyone.

This presentation will be based on this CVPR 2005 paper. You really don't need to read the paper (unless you badly want to!). Besides, I will be using slightly different notation.

There's a sizeable amount of mathematics involved. Before reading this paper, I had to revise some linear algebra and learn about Reproducing Kernel Hilbert Spaces {RKHS} (functional analysis). I suppose most of you if not all of you, are already aware of these concepts.

However, if any of you wish to have a refresher of this material, here are some excellent resources (and very small documents too):

Functional Analysis > do go through this if terms like "complete space", "Banach space", "Hilbert space of functions" etc. seem new.

Linear Algebra > you can read this if you find some terminology in the Functional Analysis document seen-before-but-quite-a-while-ago.

Finally, I am hoping that I will be able to devote minimal time to explaining what an RKHS is. Here's a document that explains it beautifully...only the first few pages are actually needed for understanding RKHS (pages 14-17 mainly)

Wahba - An Intro to Model Building with RKHS

If this seems too much, you can alternatively go through my slides on RKHS (these are also on the actual presentation).

In any case, if you wish I can go over the RKHS slides during the presentation (at the moment though, I'm not planning to).

10/1/07 2:30pm

No meeting - Mark's out of town.

10/8/07 2:30pm

(Jui-Ting Huang) One-class classification problems

10/22/07 2:30pm

Bryce practices his preliminary exam proposal.

10/29/07 2:30pm

Brief Review: Latent Semantic Analysis: towards insight into human cognition



S. Deerwester, Susan Dumais, G. W. Furnas, T. K. Landauer, R. Harshman (1990). "Indexing by Latent Semantic Analysis". Journal of the Society for Information Science 41 (6): 391-407. http://lsi.research.telcordia.com/lsi/papers/JASIS90.pdf

Mark Steyvers(2007). Probabilistic Topic Models. In T. Landauer, D. McNamara, S. Dennis & W. Kintsch (Eds.), Handbook of latent semantic analysis (pp. 467-480). Mahwah, NJ: Erlbaum. http://psiexp.ss.uci.edu/research/papers/SteyversGriffithsLSABookFormatted.pdf

11/5/07 2:30pm

Topic : Likelihood-Maximizing Beamforming

"One page summary for this topic"

"Likelihood-Maximizing Beamforming for Robust Hands-Free Speech Recognition" by M. L. Seltzer, B. Raj, and R. M. Stern, IEEE Trans. on Speech and Audio Processing, 2004.

"Subband Likelihood-Maximizing Beamforming for Speech Recognition in Reverberant Environments" by M. L. Seltzer and R. M. Stern, IEEE Trans. on Audio, Speech, and Language Processing, 2006.

11/12/07 2:30pm

Arthur practices his preliminary exam proposal.

11/19/07 2:30pm

Thanksgiving Break

11/26/07 2:30pm

12/3/07 2:30pm

12/10/07 2:30pm

Final Exams

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