We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Product recommender systems are a popular application and research field of CBR for several years now. However, almost all CBRbased recommender systems are not case-based in the or...
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...
In this paper, we present a novel segmentationinsensitive approach for mining common patterns from 2 images. We develop an algorithm using the Earth Movers Distance (EMD) framewor...