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ISL & IT Forum present "Human-Interpretable Concept Learning via Information Lattices"

Human-Interpretable Concept Learning via Information Lattices
Friday, September 6, 2019 - 1:15pm
Packard 202
Professor Lav R. Varshney (Salesforce Research & UIUC)
Abstract / Description: 

Is it possible to learn the laws of music theory directly from raw sheet music in the same human-interpretable form as a music theory textbook? How little prior knowledge needs to be encoded to do so? We consider these and similar questions in other topical domains, in developing a general framework for automatic concept learning. The basic idea is an iterative discovery algorithm that has a student-teacher architecture and that operates on a generalization of Shannon's information lattice, which itself encodes a hierarchy of abstractions and is algorithmically constructed from group-theoretic foundations. In particular, learning this hierarchy of invariant concepts involves iterative optimization of Bayesian surprise and entropy. This gives a first step towards a principled and cognitive way of automatic concept learning and knowledge discovery. We further discuss applications in computational creativity, and limit theorems for creativity.


Lav Varshney is an assistant professor of electrical and computer engineering, computer science, neuroscience, and industrial engineering at the University of Illinois at Urbana-Champaign. He is also chief scientist of Ensaras, Inc. On leave, he is currently a principal research scientist at Salesforce Research, Palo Alto, CA, focusing on AI ethics and AI for social good. He received the B.S. degree (magna cum laude) with honors from Cornell University in 2004. He received the S.M., E.E., and Ph.D. degrees from the Massachusetts Institute of Technology in 2006, 2008, and 2010, where his theses received the E. A. Guillemin Thesis Award and the J.-A. Kong Award Honorable Mention. He was a research staff member at the IBM Thomas J. Watson Research Center from 2010 until 2013, where he led the design and development of the Chef Watson computational creativity system. His research interests include information and coding theory; data science and artificial intelligence; and limits of nanoscale, social, and neural computing.

Dr. Varshney serves on the advisory board of the AI XPRIZE. He received the IBM Faculty Award in 2014 and was a finalist for the Bell Labs Prize in 2014 and 2016. He and his students have won several best paper awards, his work appears in the anthology, The Best Writing on Mathematics 2014, and he was selected to present at the 2017 World Science Festival. He appears on the List of Teachers Ranked as Excellent and has been named a Center for Advanced Study Fellow at the University of Illinois.