Abstract: Technology that accurately models, analyzes, and verifies software has come a long way since its conception several decades ago.  One mode of using such technology is to look for defects in software that has already left the hands of dev

Abstract: Regular languages exhibit considerable structure.

Abstract: We develop a framework for convexifying a fairly general class of optimization problems.

Abstract: A graph is `pseudorandom' if it appears random according to certain statistics. Recently, Conlon, Fox and Zhao proved a counting lemma, counting small graphs in $\varepsilon$-regular subgraphs of sparse pseudorandom graphs.

Abstract: In today's age we have an abundance of massive data available online. This creates fantastic opportunities for Statistical learning researchers to analyze data and estimate ongoing patterns.