40 search results - page 2 / 8 » An adaptive and dynamic dimensionality reduction method for ... |
ICDM
2002
IEEE
13 years 10 months ago
2002
IEEE
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
TKDE
2011
13 years 7 days ago
2011
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
SIAMSC
2008
13 years 5 months ago
2008
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
DAWAK
1999
Springer
13 years 9 months ago
1999
Springer
Efficient index construction in multidimensional data spaces is important for many knowledge discovery algorithms, because construction times typically must be amortized by perform...
SIGMOD
2002
ACM
14 years 5 months ago
2002
ACM
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...