[Faculty] Fwd: [SDSU-CSRC COLLOQUIUM]: "Deep Learning with Induced Priors"

[Jose Castillo]

[image: cid:image001.jpg at 01D3A3DE.7CF4C6C0]

DATE:  *Friday, March 16, 2018*



TITLE:  *Deep Learning with Induced Priors*



TIME:  *3:30PM*



LOCATION:  *GMCS 314*



SPEAKER:  *Saining Xie*
*, Doctoral StudentComputer Science, UCSD*



ABSTRACT:
Deep learning has reshaped the landscape of research and applications in
artificial intelligence. In contrast to traditional hand-crafted feature
engineering, and with the support of big-data and big-compute, the promise
and dominant paradigm of deep learning research is supervised, end-to-end
and automatic representation learning. However, to tackle many real world
problems, smart structural design decisions have to be made, oftentimes
through induced priors. Those priors can be hard-wired, or automatically
learned from the data or environment. In this talk I will introduce my
research in designing and utilizing deep learning structures for different
application scenarios in supervised learning and reinforcement learning. In
particular, I will talk about my recent work on induced priors and
structures for 3D point cloud recognition and transfer learning for
continuous control.HOST:  Xiaobai Liu







Dr. Jose E. Castillo
Director/Professor
Computational Science Research Center
5500 Campanile Drive
San Diego State University
San Diego, CA  92182-1245
(619) 59407205/3430, FAX (619) 594-2459





_______________________________________________
SDSU Computational Science Research Center
Mailing List



-- 

Jose E. Castillo  Ph.D.

Director / Professor

Computational Science Research Center

5500 Campanile Dr

San Diego State University

San Diego CA 92182-1245

619 5947205/3430, Fax 619-594-2459

 http://www.csrc.sdsu.edu/mimetic-book/
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