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BMCBI
2010
214views more  BMCBI 2010»
15 years 4 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
15 years 8 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
ECML
2004
Springer
15 years 10 months ago
A Boosting Approach to Multiple Instance Learning
In this paper we present a boosting approach to multiple instance learning. As weak hypotheses we use balls (with respect to various metrics) centered at instances of positive bags...
Peter Auer, Ronald Ortner
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 7 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
15 years 10 months ago
Adaptive Blocking: Learning to Scale Up Record Linkage
Many information integration tasks require computing similarity between pairs of objects. Pairwise similarity computations are particularly important in record linkage systems, as...
Mikhail Bilenko, Beena Kamath, Raymond J. Mooney