A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing, and independence testing....
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fu...
A new iterative method for finding the projection onto the intersection of two closed convex sets in a Hilbert space is presented. It is a Haugazeau-like modification of a recentl...
Heinz H. Bauschke, Patrick L. Combettes, D. Russel...
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
Periodic smoothing splines appear for example as generators of closed, planar curves, and in this paper they are constructed using a controlled two point boundary value problem in...
Hiroyuki Kano, Magnus Egerstedt, Hiroyuki Fujioka,...
We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and support-vector clustering. Like the latter, it associates every data poin...
The physical properties of color are usually described by their spectra, eigenvector expansions or low-dimensional descriptors such as RGB or CIE-Lab. In the first part of the pap...