Randomized communication versus partition number
We show that randomized communication complexity can be superlogarithmic in the partition number of the associated communication matrix, and we obtain near-optimal randomized lower bounds for the Clique versus Independent Set problem. These results strengthen the deterministic lower bounds obtained in prior work (Göös, Pitassi, and Watson, FOCS'15). One of our main technical contributions states that information complexity when the cost is measured with respect to only 1-inputs (or only 0-inputs) is essentially equivalent to information complexity with respect to all inputs.
ACM Transactions on Computation Theory
Göös, M., Jayram, T., Pitassi, T., & Watson, T. (2018). Randomized communication versus partition number. ACM Transactions on Computation Theory, 10 (1) https://doi.org/10.1145/3170711