[Compstats] Google-UW Machine Learning Seminar: Tuesday @ 2pm MC5158

Pascal Poupart ppoupart at cs.uwaterloo.ca
Tue Sep 14 08:17:00 EDT 2010

  Quick reminder that Yee Whye Teh's talk is today at 2pm in MC5158.  
Grad students are also invited to meet with Yee Whye on Wednesday at 2pm 
in DC2314.

cheers, Pascal

On 9/10/2010 12:04 PM, Pascal Poupart wrote:
>  Google-UW Machine Learning Seminar
> Hierarchical Bayesian Models of Language and Text (Yee Whye Teh)
> http://compstats.uwaterloo.ca/google
> One of our alumni, Yee Whye Teh (now at University College London), 
> will give an invited talk in the Google-UW Machine Learning seminar 
> series on Tuesday @ 2pm in MC5158.  Yee Whye is a rising star who 
> advanced and popularized the use of hierarchical Bayesian techniques 
> in Natural Language Processing and Machine Learning.  I encourage 
> everyone to attend (see abstract below).
> cheers, Pascal
> =============================
> Title: Hierarchical Bayesian Models of Language and Text
> http://compstats.uwaterloo.ca/google
> Speaker: Yee Whye Teh (University College London)
> Date: Tuesday, September 14
> Time: 2 pm
> Location: MC5158
> Abstract:
> In this talk I will present a new approach to modelling sequence data 
> called the sequence memoizer. As opposed to most other sequence 
> models, our model does not make any Markovian assumptions. Instead, we 
> use a hierarchical Bayesian approach which enforces sharing of 
> statistical strength across the different parts of the model. To make 
> computations with the model efficient, and to better model the 
> power-law statistics often observed in sequence data, we use a 
> Bayesian nonparametric prior called the Pitman-Yor process as building 
> blocks in the hierarchical model. We show state-of-the-art results on 
> language modelling and text compression.
> This is joint work with Frank Wood, Jan Gasthaus, Cedric Archambeau 
> and Lancelot James.
> Biography:
> Yee Whye Teh is a Lecturer (equivalent to an assistant professor in US 
> system) at the Gatsby Computational Neuroscience Unit, UCL. He is 
> interested in machine learning and Bayesian statistics. His current 
> focus is on developing Bayesian nonparametric methodologies for 
> unsupervised learning, computational linguistics, and genetics. Prior 
> to his appointment he was Lee Kuan Yew Postdoctoral Fellow at the 
> National University of Singapore and a postdoctoral fellow at 
> University of California at Berkeley. He obtained his Ph.D. in 
> Computer Science at the University of Toronto in 2003. He is programme 
> co-chair of AISTATS 2010.

Pascal Poupart
Associate Professor
David R. Cheriton School of Computer Science
University of Waterloo
200 University Avenue West
Waterloo, Ontario
Canada N2L 3G1
Web: http://www.cs.uwaterloo.ca/~ppoupart
Email: ppoupart at cs.uwaterloo.ca
Telephone: 1-519-888-4567x36239
Fax: 1-519-885-1208

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