A product-moment method with a random index subset yields new concentration bounds for read-Δ families under limited independence and for linear hashing with entropy-rich inputs, and recovers Markov-chain concentration scales.
Proceedings of the 35th Annual Symposium on Foundations of Computer Science (FOCS) , pages =
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Concentration from Product Moments via an Additional Element of Randomness
A product-moment method with a random index subset yields new concentration bounds for read-Δ families under limited independence and for linear hashing with entropy-rich inputs, and recovers Markov-chain concentration scales.