What are Wasserstein and Earth Movers Distances 🌱

What is Wasserstein distance

Let(X,d) be a Polish metric space, and let p[1,). For any two probability measures μ,ν on X, the Wasserstein distance of order p between μ and ν is defined by the formula Wp(μ,ν)=(infπΠ(μ,ν)Xd(x,y)pdπ(x,y))1/p=inf{[Ed(X,Y)p]1p,law(X)=μ,law(Y)=ν}

Wp(μ0,ν)=inf{E[d(X0,X1)p]1/pX0 comes from μ and X1 comes from ν}

What is the Earth Mover’s Distance

Finally, the Earth Mover (EM) (version of Wasserstein distance): Let Π(Pr,Pg) be the set of all joint distributions γ whose marginal distributions are Pr and Pg. Then. W(Pr,Pg)=infγΠ(Pr,Pg)E(x,y)γ[xy]

First, the intuitive goal of the EM distance. Probability distributions are defined by how much mass they put on each point. Imagine we started with distribution Pr, and wanted to move mass around to change the distribution into Pg. Moving mass m by distance d costs md effort. The earth mover distance is the minimal effort we need to spend. Why does the infimum over Π(Pr,Pg) give the minimal effort? You can think of each γΠ as a transport plan. To execute the plan, for all x,y move γ(x,y) mass from x to y Every strategy for moving weight can be represented this way. But what properties does the plan need to satisfy to transform Pr into Pg? The amount of mass that leaves x is yγ(x,y)dy. This must equal Pr(x), the amount of mass originally at x. The amount of mass that enters y is xγ(x,y)dx. This must equal Pg(y), the amount of mass that ends up at y. This shows why the marginals of γΠ must be Pr and Pg. For scoring, the effort spent is xyγ(x,y)|xy|dydx=E(x,y)γ[|xy|] Computing the infinum of this over all valid γ gives the earth mover distance.

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