Sciweavers

2826 search results - page 46 / 566
» Maximal Vector Computation in Large Data Sets
Sort
View
TKDE
2011
168views more  TKDE 2011»
13 years 4 months ago
On Computing Farthest Dominated Locations
—In reality, spatial objects (e.g., hotels) not only have spatial locations but also have quality attributes (e.g., price, star). An object p is said to dominate another one p , ...
Hua Lu, Man Lung Yiu
APPT
2005
Springer
14 years 2 months ago
Principal Component Analysis for Distributed Data Sets with Updating
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Zheng-Jian Bai, Raymond H. Chan, Franklin T. Luk
APWEB
2010
Springer
14 years 12 days ago
Computing Large Skylines over Few Dimensions: The Curse of Anti-correlation
The skyline of a set P of multi-dimensional points (tuples) consists of those points in P for which no clearly better point in P exists, using component-wise comparison on domains ...
Henning Köhler, Jing Yang
NIPS
2008
13 years 10 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman
ALMOB
2006
89views more  ALMOB 2006»
13 years 9 months ago
On the maximal cliques in c-max-tolerance graphs and their application in clustering molecular sequences
Given a set S of n locally aligned sequences, it is a needed prerequisite to partition it into groups of very similar sequences to facilitate subsequent computations, such as the ...
Katharina Anna Lehmann, Michael Kaufmann, Stephan ...