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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
15 years 10 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
BMCBI
2010
141views more  BMCBI 2010»
14 years 9 months ago
Computing and visually analyzing mutual information in molecular co-evolution
Background: Selective pressure in molecular evolution leads to uneven distributions of amino acids and nucleotides. In fact one observes correlations among such constituents due t...
Sebastian Bremm, Tobias Schreck, Patrick Boba, Ste...
BMCBI
2006
100views more  BMCBI 2006»
14 years 9 months ago
Empirical array quality weights in the analysis of microarray data
Background: Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or &qu...
Matthew E. Ritchie, Dileepa S. Diyagama, Jody Neil...
ICCV
2007
IEEE
15 years 11 months ago
Capacity Scaling for Graph Cuts in Vision
Capacity scaling is a hierarchical approach to graph representation that can improve theoretical complexity and practical efficiency of max-flow/min-cut algorithms. Introduced by ...
Olivier Juan, Yuri Boykov