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» Efficient Discovery of Confounders in Large Data Sets
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BMCBI
2011
15 years 21 days ago
A theoretical entropy score as a single value to express inhibitor selectivity
Background: Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effect...
Joost C. M. Uitdehaag, Guido J. R. Zaman
NEUROSCIENCE
2001
Springer
15 years 10 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
ICDE
2003
IEEE
170views Database» more  ICDE 2003»
16 years 7 months ago
Keyword Proximity Search on XML Graphs
XKeyword provides efficient keyword proximity queries on large XML graph databases. A query is simply a list of keywords and does not require any schema or query language knowledg...
Vagelis Hristidis, Yannis Papakonstantinou, Andrey...
ICML
2009
IEEE
16 years 7 months ago
Prototype vector machine for large scale semi-supervised learning
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
Kai Zhang, James T. Kwok, Bahram Parvin
WWW
2009
ACM
16 years 6 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel