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» Optimization of in-network data reduction
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IWPEC
2010
Springer
14 years 7 months ago
Partial Kernelization for Rank Aggregation: Theory and Experiments
RANK AGGREGATION is important in many areas ranging from web search over databases to bioinformatics. The underlying decision problem KEMENY SCORE is NP-complete even in case of fo...
Nadja Betzler, Robert Bredereck, Rolf Niedermeier
BMCBI
2008
142views more  BMCBI 2008»
14 years 9 months ago
Optimal neighborhood indexing for protein similarity search
Background: Similarity inference, one of the main bioinformatics tasks, has to face an exponential growth of the biological data. A classical approach used to cope with this data ...
Pierre Peterlongo, Laurent Noé, Dominique L...
NPL
2006
130views more  NPL 2006»
14 years 9 months ago
A Fast Feature-based Dimension Reduction Algorithm for Kernel Classifiers
This paper presents a novel dimension reduction algorithm for kernel based classification. In the feature space, the proposed algorithm maximizes the ratio of the squared between-c...
Senjian An, Wanquan Liu, Svetha Venkatesh, Ronny T...
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IPPS
2005
IEEE
15 years 3 months ago
Designing Scalable FPGA-Based Reduction Circuits Using Pipelined Floating-Point Cores
The use of pipelined floating-point arithmetic cores to create high-performance FPGA-based computational kernels has introduced a new class of problems that do not exist when usi...
Ling Zhuo, Gerald R. Morris, Viktor K. Prasanna
AAAI
2010
14 years 11 months ago
Multi-Instance Dimensionality Reduction
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Yu-Yin Sun, Michael K. Ng, Zhi-Hua Zhou