# Advances in interactive Knowledge Discovery and Data Mining in complex and big data sets (15w2181)

Arriving in Banff, Alberta Friday, July 24 and departing Sunday July 26, 2015

## Organizers

(University of Bologna)

(University of Alberta)

(Medical University Graz)

Several problems arise from such settings. One, in the application context, is the choice of suitable functions f. This is generally done heuristically, but it would be necessary to have parameterized spaces of such functions and, eventually, a self-driving, optimized choice of f for statistical learning. Another challenge is the construction of good distances. The ones presently available need exponential computation. A third problem concerns functions with multidimensional range: functions from X to R give rise to diagrams whose information is condensed in a discrete (mostly finite) set of points in the plane; but, if the range is $mathbb{R^{k}}$, the same information is carried by (2k-2) dimensional patches in $mathbb{R^{2k}}$. A one-dimensional reduction is available, but it raises computational problems in applications.