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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 7 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 7 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
WSDM
2010
ACM
204views Data Mining» more  WSDM 2010»
16 years 2 months ago
Learning URL patterns for webpage de-duplication
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we pres...
Hema Swetha Koppula, Krishna P. Leela, Amit Agarwa...
ATAL
2009
Springer
16 years 1 months ago
Learning equilibria in repeated congestion games
While the class of congestion games has been thoroughly studied in the multi-agent systems literature, settings with incomplete information have received relatively little attenti...
Moshe Tennenholtz, Aviv Zohar
ITICSE
2009
ACM
16 years 1 months ago
Relating research and teaching: learning from experiences and beliefs
The relationship between research and teaching has possible benefits and inherent tensions. Exploring the potentially beneficial relationship is of interest and possible value to ...
Su White, Alastair Irons