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NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
ATAL
2010
Springer
13 years 9 months ago
Deception in networks of mobile sensing agents
Recent studies have investigated how a team of mobile sensors can cope with real world constraints, such as uncertainty in the reward functions, dynamically appearing and disappea...
Viliam Lisý, Roie Zivan, Katia P. Sycara, M...
BMCBI
2011
13 years 1 days ago
Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis
Background: Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these patholog...
Lionel Blanchet, Agnieszka Smolinska, Amos Attali,...
PLDI
2009
ACM
14 years 3 months ago
A language for information flow: dynamic tracking in multiple interdependent dimensions
This paper presents λI , a language for dynamic tracking of information flow across multiple, interdependent dimensions of information. Typical dimensions of interest are integr...
Avraham Shinnar, Marco Pistoia, Anindya Banerjee
ICSEA
2007
IEEE
14 years 2 months ago
Test Data Generation from UML State Machine Diagrams using GAs
Automatic test data generation helps testers to validate software against user requirements more easily. Test data can be generated from many sources; for example, experience of t...
Chartchai Doungsa-ard, Keshav P. Dahal, M. Alamgir...