Distance measures for point sets and their computation

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Learning Theory for Distribution Regression (2014, background): “There also exist other (semi)metric constructions on points sets (Eiter and Mannila, 1997; Ramon and Bruynooghe, 2001).”
Data-driven structural priors for shape completion (2015, methodology): “As part parameters change the correspondences between points and parts (ESMD) and the notion of symmetric points (Esymm) change as well.”
A polynomial time computable metric between point sets (2001, methodology): “Eiter andMannila [5] also discuss a family of Manhattan measures between sets which we can describe as instances of the following scheme: dβ(A,B) = min r∈mβ(A,B) d(r,A,B) where d(r,A,B) = ∑ (x,y)∈r d(x, y) + #(B \ r(A)) + #(A \ r−1(B)) 2 .”
Using Semantic Roles to Improve Question Answering (2007, methodology): “Speciﬁcally, we model the interaction between all pairwise labeling decisions as a minimum weight bipartite edge cover problem (Eiter and Mannila, 1997; Cormen et al., 1990).”