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» Making inferences with small numbers of training sets
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CIKM
2001
Springer
14 years 1 months ago
Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering
Collaborative filtering uses a database about consumers’ preferences to make personal product recommendations and is achieving widespread success in both E-Commerce and Informat...
Kai Yu, Xiaowei Xu, Martin Ester, Hans-Peter Krieg...
KAIS
2000
106views more  KAIS 2000»
13 years 8 months ago
FANNC: A Fast Adaptive Neural Network Classifier
In this paper, a fast adaptive neural network classifier named FANNC is proposed. FANNC exploits the advantages of both adaptive resonance theory and field theory. It needs only on...
Zhi-Hua Zhou, Shifu Chen, Zhaoqian Chen
BMCBI
2010
132views more  BMCBI 2010»
13 years 9 months ago
Consistency, comprehensiveness, and compatibility of pathway databases
Background: It is necessary to analyze microarray experiments together with biological information to make better biological inferences. We investigate the adequacy of current bio...
Donny Soh, Difeng Dong, Yike Guo, Limsoon Wong
ISCC
2006
IEEE
133views Communications» more  ISCC 2006»
14 years 2 months ago
Choosing Weights for IP Network Dimensioning Optimization
Often in Internet Protocol (IP) networks, links are assigned weights, and traffic demands are routed along shortest paths. Hence, these link weights are the parameters which dete...
Olivier Klopfenstein, Sebastien Mamy
APPROX
2008
Springer
101views Algorithms» more  APPROX 2008»
13 years 11 months ago
Streaming Algorithms for k-Center Clustering with Outliers and with Anonymity
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...
Richard Matthew McCutchen, Samir Khuller