Randomized rounding: a technique for provably good algorithms and algorithmic proofs
Combinatorica - Theory of Computing
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Balls and bins: a study in negative dependence
Random Structures & Algorithms
Dependent Rounding in Bipartite Graphs
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Distributions on Level-Sets with Applications to Approximation Algorithms
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Negative dependence and srinivasan's sampling process
Combinatorics, Probability and Computing
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We study negative dependence properties of a sampling process due to Srinivasan to produce distributions on level sets with given marginals. We give a simple proof that the distribution satisfies negative association. We also show that under a linear match schedule it satisfies the stronger condition of conditional negative association via a non-trivial application of the Feder–Mihail theorem. This method involves the notion of a variable of positive influence. We give some results and related counter-examples which might shed some light on its role in a theory of negative dependence.