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cs.DS2024
Improved parallel derandomization via finite automata with applications
Jeff Giliberti, David G. Harris
A central approach to algorithmic derandomization is to construct probability distributions with small support that "fool" randomized algorithms, often enabling efficient parallel…
cs.DS2024
Massively Parallel Ruling Set Made Deterministic
Jeff Giliberti, Zahra Parsaeian
We study the deterministic complexity of the -Ruling Set problem in the model of Massively Parallel Computation (MPC) with linear and strongly sublinear local memory. Linear MPC…