PhD Seminar • Artificial Intelligence • ML-Driven Algorithm Selection and Meta-Solving for Hard Combinatorial ProblemsExport this event to calendar

Wednesday, October 26, 2022 — 4:00 PM to 5:00 PM EDT

Please note: This PhD seminar will take place online.

Joseph Scott, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Vijay Ganesh

On hard search problems, no single algorithm is expected to be the fastest on all inputs. For example, in practice, SAT/SMT solvers deploy several strategies ranging from algorithm selection to solver portfolios. In this talk, I’ll present two tools, MachSMT — an algorithm selection tool for Satisfiability Modulo Theories (SMT) solvers, and Goose — an adaptive algorithm selection tool, which we dub a meta-solver, for deep neural network verification.


To join this PhD seminar on Zoom, please go to https://us02web.zoom.us/j/5330049001?pwd=OVVDN1JPN2RmRzV6S2dmejFMM0RpQT09.

Location 
Online PhD seminar
200 University Avenue West

Waterloo, ON N2L 3G1
Canada
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