30 search results - page 3 / 6 » Locally linear metric adaptation for semi-supervised cluster... |
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
K-Nearest Neighbors relies on the definition of a global metric. In contrast, Discriminant Adaptive Nearest Neighbor (DANN) computes a different metric at each query point based o...
PARA
2000
Springer
13 years 9 months ago
2000
Springer
Abstract. Distributed cluster environments are becoming popular platforms for high performance computing in lieu of single-vendor supercomputers. However, the reliability and susta...
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...
FSKD
2006
Springer
13 years 9 months ago
2006
Springer
Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional spac...
CIKM
2006
Springer
13 years 9 months ago
2006
Springer
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...