On concentration of the empirical measure for general transport costs
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Let μ be a probability measure on ℝ^d and μ_N its empirical measure with sample size N. We prove a concentration inequality for the optimal transport cost between μ and μ_N for cost functions with polynomial local growth, that can have superpolynomial global growth. This result generalizes and improves upon estimates of Fournier and Guillin. The proof combines ideas from empirical process theory with known concentration rates for compactly supported μ. By partitioning ℝ^d into annuli, we infer a global estimate from local estimates on the annuli and conclude that the global estimate can be expressed as a sum of the local estimate and a mean-deviation probability for which efficient bounds are known.
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