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» Informative sampling for large unbalanced data sets
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FOIKS
2008
Springer
16 years 10 days ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
144
Voted
BMCBI
2006
144views more  BMCBI 2006»
15 years 3 months ago
Development and implementation of an algorithm for detection of protein complexes in large interaction networks
Background: After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry e...
Md. Altaf-Ul-Amin, Yoko Shinbo, Kenji Mihara, Ken ...
IS
2006
15 years 3 months ago
High dimensional nearest neighbor searching
As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of mult...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...
BMCBI
2005
103views more  BMCBI 2005»
15 years 3 months ago
Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery
Background: Molecular profiling generates abundance measurements for thousands of gene transcripts in biological samples such as normal and tumor tissues (data points). Given such...
Leslie Grate
147
Voted
WSC
2007
15 years 5 months ago
New greedy myopic and existing asymptotic sequential selection procedures: preliminary empirical results
Statistical selection procedures can identify the best of a finite set of alternatives, where “best” is defined in terms of the unknown expected value of each alternative’...
Stephen E. Chick, Jürgen Branke, Christian Sc...