Let X1, X2, . . . , Xk be independent n bit random variables. If they have arbitrary distributions, we show how to compute distributions like Pr{X1 ⊕ X2 ⊕ · · · ⊕ Xk} and ...
This paper connects two fundamental ideas from theoretical computer science: hard-core set construction, a type of hardness amplification from computational complexity, and boosti...
— We explore an online problem where a group of robots has to find a target whose position is unknown in an unknown planar environment whose geometry is acquired by the robots d...
We exhibit an explicitly computable ‘pseudorandom’ generator stretching l bits into m(l) = lΩ(log l) bits that look random to constant-depth circuits of size m(l) with log m...
We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...