Random Structures & Algorithms - Probabilistic methods in combinatorial optimization
Large deviations for sums of partly dependent random variables
Random Structures & Algorithms - Isaac Newton Institute Programme “Computation, Combinatorics and Probability”: Part I
Journal of the ACM (JACM)
Randomness-efficient oblivious sampling
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
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In this note we prove a large deviation bound on the sum of random variables with the following dependency structure: there is a dependency graph G with a bounded chromatic number, in which each vertex represents a random variable. Variables that are represented by neighboring vertices may be arbitrarily dependent, but collections of variables that form an independent set in G are t-wise independent.