Kavli Institute NeuroLunch

Sponsored by KIBS and the NeuroTechnology Center
February 2, 2016

Tuesday, February 2nd, 2016

Kui Tang (PhD Candidate), Jebara Lab

"Bethe Learning of Graphical Models via MAP Decoding"

Speaker Bio:
I am a second year PhD student in Computer Science at Columbia University.

Presentation Summary:
Graphical models are a flexible and powerful method to model high-dimensional correlated data, including images and measurements of neural activity. Traditionally, these methods are computationally expensive. I will present a novel state of the art approximate algorithm for learning graphical models based on convex optimization principles that leveraged recently developed specialized linear programming solvers. I will conclude with applications from news and financial data and neuroscience. Joint work with Nicholas Ruozzi, David Belanger, and Prof. Tony Jebara.


Rm. 900 Sherman Fairchild Bldg. - Note the new room location
12:00 pm - 1:00pm
1212 Amsterdam Ave.
New York, NY 10027