Shifting proximities

Support Vector Machine Classifiers for Asymmetric Proximities

The aim of this paper is to afford classification tasks on asymmetric kernel matrices using Support Vector Machines (SVMs). Ordinary theory for SVMs requires to work with symmetric proximity matrices. In this work we examine the performance of several symmetrization methods in classification tasks. In addition we propose a new method that specifically takes classification labels into account to...

Spatio-temporal Proximities for Multimedia Document Adaptation

Distance Metric Learning from Pairwise Proximities

We compare techniques for embedding a data set into Euclidean space under different notions of proximity constraints.

Visualizing asymmetric proximities with MDS models

Zero-dimensional proximities and zero-dimensional compactifications

Article history: Received 4 August 2008 Received in revised form 12 December 2008 Accepted 13 December 2008 MSC: 54E05 54D35 54G05