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» Maximal Vector Computation in Large Data Sets
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ICASSP
2011
IEEE
14 years 8 months ago
Discriminative simplification of mixture models
Simplification of mixture models has recently emerged as an important issue in the field of statistical learning. The heavy computational demands of using large order models dro...
Yossi Bar-Yosef, Yuval Bistritz
IPPS
2002
IEEE
15 years 9 months ago
Communication Characteristics of Large-Scale Scientific Applications for Contemporary Cluster Architectures
This paper examines the explicit communication characteristics of several sophisticated scientific applications, which, by themselves, constitute a representative suite of publicl...
Jeffrey S. Vetter, Frank Mueller
DMIN
2006
144views Data Mining» more  DMIN 2006»
15 years 5 months ago
Discovering Assignment Rules in Workforce Schedules Using Data Mining
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...
Jihong Yan
EDBT
2009
ACM
277views Database» more  EDBT 2009»
15 years 9 months ago
G-hash: towards fast kernel-based similarity search in large graph databases
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
AUSAI
2003
Springer
15 years 9 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra