[AI Seminar] AI Lunch - Room Change and Talk Information

Ellen Vitercik vitercik at cs.cmu.edu
Mon Jan 11 09:17:21 EST 2016

Dear faculty and students,

We look forward to seeing you tomorrow, Tuesday, January 12th, at noon for
the first AI lunch <http://www.cs.cmu.edu/~aiseminar/> of the semester.
There is a room change -- we will meet in *GHC 6115.*

Jun Zhu <http://bigml.cs.tsinghua.edu.cn/~jun/index.shtml> will speak
about Scalable Bayesian Inference with Posterior Regularization. Below is a
talk abstract and speaker bio.

*Abstract:* Bayesian methods represent one important type of statistical
methods for learning, inference and decision making. At the core is Bayes'
theorem, which has been developed for more than 250 years. However, in the
Big Data era, many challenges need to be addressed, ranging from theory,
algorithm, and applications. In this talk, I will introduce some recent
developments on Bayesian inference with posterior regularization, which can
incorporate rich side information such as the large-margin property we like
to impose on the model distribution for accurate prediction, or the domain
knowledge collected from experts or crowds for good interpretation, and
scalable online learning and distributed inference algorithms. When applied
to deep generative models, we are able to significantly improve the
prediction accuracy without sacrificing the generative performance.

*Bio: *Dr. Jun Zhu is an associate professor at Department of Computer
Science and Technology, Tsinghua University, and an adjunct faculty at
Machine Learning Department, Carnegie Mellon University. He received his
Ph.D. in Computer Science from Tsinghua in 2009. Before joining Tsinghua in
2011, he did post-doctoral research in CMU. His research interest lies in
developing scalable machine learning methods to understand complex
scientific and engineering data. Dr. Zhu has published over 60
peer-reviewed papers in the prestigious conferences and journals. He is an
associate editor for IEEE Trans. on PAMI. He served as area chair for ICML,
NIPS, UAI, IJCAI and AAAI. He was a local chair of ICML 2014. He is a
recipient of the IEEE Intelligent Systems "AI's 10 to Watch" Award, NSFC
Excellent Young Scholar Award, and CCF Young Scientist Award. His work is
supported by the "221 Basic Research Plan for Young Talents" at Tsinghua.


Ellen and Ariel
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