[AI Seminar] AI Seminar sponsored by Fortive on Jan 21 (NSH 3305) -- Yichong Xu -- Efficient Learning from Diverse Sources of Information

[Aayush Bansal]

Yichong Xu will be giving a seminar on  "Efficient Learning from Diverse
Sources of Information" from *12:00 - 01:00 PM* in Newell Simon Hall (NSH)
3305.

CMU AI Seminar is sponsored by Fortive. Lunch will be served.

Following are the details of the talk:

*Title: *Efficient Learning from Diverse Sources of Information

*Abstract:* Although machine learning has witnessed rapid progress in the
last decade, many current learning algorithms are very inefficient in terms
of the amount of data it uses, and the time used to train the model. On the
other hand, humans excel at many of the learning tasks with very limited
data. Why are machines so inefficient, and why can humans learn so well?
The key to the answer lies in that humans can learn from diverse sources of
information, and are able to use past knowledge to apply in new domains. In
this talk, I will study learning from diverse sources of information to
make ML algorithms more efficient. In the first part, I will talk about how
to incorporate diverse forms of questions into the learning process.
Particularly, I will look at the problem of utilizing preference
information for learning a regression function and show an interesting
connection to nearest neighbors and isotonic regression. In the second
part, I will talk about multitask and transfer learning from different
domains for natural language understanding. I will explain a
sample-reweighting scheme using language models to automatically weight
external-domain samples according to their help for the target task.

*Bio*: Yichong Xu is a Ph.D. student in Machine Learning Department of
Carnegie Mellon University. He works on machine learning, especially on
interactive learning problems, with his advisors Profs. Artur Dubrawski and
Aarti Singh.

To learn more about the seminar series, please visit the website
<http://www.cs.cmu.edu/~aiseminar/>.

-- 
Aayush Bansal
http://www.cs.cmu.edu/~aayushb/
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