Theory of Computing Seminar
Annenberg 213
Detection of Planted Solutions for Flat Satisfiability Problems
Quentin Berthet,
Caltech,
Abstract:
We study the detection problem of finding planted solutions in random instances of flat satisfiability problems, a generalization of boolean satisfiability formulas. We describe the properties of random instances
of flat satisfiability, as well of the optimal rates of detection of the associated hypothesis testing problem. We also study the performance of an algorithmically efficient testing procedure. Introducing a modification of our model, the light planting of solutions, allows us to hint strongly at the difficulty of detecting planted flat satisfiability for a wide class of tests, by relating this problem to learning parity with noise.
of flat satisfiability, as well of the optimal rates of detection of the associated hypothesis testing problem. We also study the performance of an algorithmically efficient testing procedure. Introducing a modification of our model, the light planting of solutions, allows us to hint strongly at the difficulty of detecting planted flat satisfiability for a wide class of tests, by relating this problem to learning parity with noise.
For more information, please contact Thomas Vidick by email at vidick@cms.caltech.edu.
Event Series
Theory of Computing Seminar Series