80 search results - page 2 / 16 » Conservative Adaptation in Metric Spaces |
ICMLC
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
CVPR
2001
IEEE
14 years 7 months ago
2001
IEEE
This paper presents a new approach to ranking relevant images for retrieval. Distance in the feature space associated with a kernel is used to rank relevant images. An adaptive qu...
STACS
2007
Springer
13 years 11 months ago
2007
Springer
The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
CEC
2007
IEEE
13 years 9 months ago
2007
IEEE
Existing niching techniques commonly use the Euclidean distance metric in the decision space for the classification of feasible solutions to the niches under formation. This approa...
SOFSEM
2007
Springer
13 years 11 months ago
2007
Springer
Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, ca...