In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Let X be a compact metric space. A closed set K X is located if the distance function d(x, K) exists as a continuous realvalued function on X; weakly located if the predicate d(x,...
Motivation: Finding a good network null model for protein-protein interaction (PPI) networks is a fundamental issue. Such a model would provide insights into the interplay between...
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
In [8, 6] we introduced a family of `modal' languages intended for talking about distances. These languages are interpreted in `distance spaces' which satisfy some (or a...
Oliver Kutz, Holger Sturm, Nobu-Yuki Suzuki, Frank...