Discrete Mathematics Seminar 

Speaker: Bernard Lidicky
Title: Pattern Boost and Axplorer
Abstract: Pattern Boost is a method developed for finding combinatorial constructions using machine learning. It combines local search and machine learning. It alternates between training a neural network to make examples and optimizing these examples using local search. While local search can get stuck in local optima easily, the neural network may extract some patters in the good constructions that help overcome the local optima problem. The original idea of Pattern Boost was recently reimplemented as Axplorer.
The aim of the talk is to introduce the main ideas behind the tools and how to use them. This is not a talk discussing research or results of the speaker.