Direct Sums in Randomized Communication Complexity

COMPUTER SCIENCE/DISCRETE MATH II
Topic:Direct Sums in Randomized Communication Complexity
Speaker:Anup Rao
Affiliation:Member, School of Mathematics
Date:Tuesday, March 24
Time/Room:10:30am - 12:30pm/S-101

Does computing n copies of a function require n times the computational effort? In this work, we give the first non-trivial answer to this question for the model of randomized communication complexity. We show that: 1. Computing n copies of a function requires sqrt{n} times the communication. 2. For average case complexity, given any distribution mu on inputs, computing n copies of the function on n independent inputs sampled according to mu requires at least sqrt{n} times the communication for computing one copy. 3. If mu is a product distribution, computing n copies on n independent inputs sampled according to mu requires n times the communication. We also study the complexity of computing the parity of n evaluations of f, and obtain results analogous to those above. Our results are obtained by designing compression schemes for communication protocols that can be used to compress the communication in a protocol that does not transmit a lot of information about its inputs. This is joint work with Boaz Barak, Mark Braverman and Xi Chen.