OptimalAI
Authors
Mark Herbster
Guy Lever
John Shawe-Taylor
Fabio Vitale
Fabio Vitale
Publication date
2011
Publisher
Total citations
Cited by
Description
Data-Dependent Geometries and Structures : Analyses and Algorithms for Machine Learning
Page 1 Data-Dependent Geometries and Structures : Analyses and Algorithms for Machine
Learning Mark Herbster, Guy Lever, John Shawe-Taylor University College London
m.herbster@cs.ucl.ac.uk g.lever@cs.ucl.ac.uk jst@cs.ucl.ac.uk Claudio Gentile, Fabio Vitale
Universita’ dell’Insubria, Varese claudio.gentile@uninsubria.it, fabiovdk@yahoo.com Nello
Cristianini University of Bristol nello.cristianini@gmail.com 29th March 2012 Page 2 Data
Dependent Geometry What is a “data-dependent geometry”? Standard paradigm A dataset is
sampled from a space with a given geometry the “distances” between particular points is
independent of the sample Data-dependent paradigm A dataset is sampled from a space with an
unknown geometry Hence the “distances” between particular points is dependent on the sample …