[Lisa_seminaires] [DIRO Talk] Jacob Andreas (UC Berkeley) Mon Feb 26 11AM Z240

Michael Noukhovitch mnoukhov at gmail.com
Ven 23 Fév 12:29:08 EST 2018


Kicking off next week's special DIRO talks we have *Jacob Andreas* from *UC
Berkeley* giving a talk on *Monday Feb 26* at *11:00AM* in room
*Claire-McNicoll
Z240*.

You should be able to learn quite a bit from this presentation just by
listening!
Michael

*TITLE *Learning from Language

*KEYWORDS *NLP, compositional/modular learning, reinforcement learning,
interpretable ML


*ABSTRACT*Natural language is built from a library of concepts and
compositional
operators that provide a rich source of information about how humans
understand the world.  Can this information help us build better
machine learning models? In this talk, we'll explore three ways of
integrating compositional linguistic structure and learning: using
language as a source of modular reasoning operators for question
answering, as a scaffold for fast and generalizable reinforcement
learning, and as a tool for understanding representations in neural
networks.

*BIO*
Jacob Andreas is a fifth-year PhD student at UC Berkeley working in
natural language processing. He holds a B.S. from Columbia and an
M.Phil. from Cambridge, where he studied as a Churchill scholar. His
papers were recognized at NAACL 2016 and ICML 2017. Jacob has been an
NSF graduate fellow, a Huawei--Berkeley AI fellow, and a Facebook
fellow.
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