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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Apr 14, 2021 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kuldeep Meel, Department of Computer Science, School of Computing at National University of Singapore
Talk Title: Scalable Functional Synthesis: The Child of Perfect Marriage between Machine Learning and Formal Methods
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Don't we all dream of the perfect assistant whom we can just tell what to do, and the assistant can figure out how to accomplish the tasks? Formally, given a specification F(X, Y) over the set of input variables X and output variables Y, we want the assistant, aka functional synthesis engine, to design a function G such that (X, Y=G(X)) satisfies F. Functional synthesis has been studied for over 150 years, dating back to Boole in 1850s and yet scalability remains a core challenge. Motivated by progress in machine learning, we design a new algorithmic framework, Manthan, which views functional synthesis as a classification problem, relying on advances in constrained sampling for data generation, and advances in automated reasoning for a novel proof-guided refinement and provable verification. On an extensive and rigorous evaluation over 609 benchmarks, we demonstrate that Manthan significantly improves upon the current state of the art. The significant performance improvements, along with our detailed analysis, highlights several interesting avenues of future work at the intersection of machine learning, constrained sampling, and automated reasoning.
Biography: Kuldeep Meel is the Sung Kah Kay Assistant Professor in the Computer Science Department of the School of Computing at the National University of Singapore where he also holds the President's Young Professorship. His research interests lie at the intersection of Formal Methods and Artificial Intelligence. He is a recipient of the 2019 NRF Fellowship for AI and was named AI's 10 to Watch by IEEE Intelligent Systems in 2020. His work received the 2018 Ralph Budd Award for Best PhD Thesis in Engineering, 2014 Outstanding Masters Thesis Award from Vienna Center of Logic and Algorithms and Best Student Paper Award at CP 2015. He received his Ph.D. (2017) and M.S. (2014) degree from Rice University, and B. Tech. (with Honors) degree (2012) in Computer Science and Engineering from Indian Institute of Technology, Bombay.
Host: pierluigi Nuzzo, nuzzo@usc.edu
Webcast: https://usc.zoom.us/webinar/register/WN_Qk4-7AthThudso7LXs2OiALocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_Qk4-7AthThudso7LXs2OiA
Audiences: Everyone Is Invited
Contact: Talyia White