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CVPR
2006
IEEE
14 years 10 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
ICIP
2008
IEEE
14 years 10 months ago
Robust brain activation detection in functional MRI
Functional Magnetic Resonance Imaging (MRI) is today one of the most important non-invasive tools to study the brain from a functional point of view. The blood-oxygenation-level-d...
David M. Afonso, João M. Sanches, Martin H....
RECOMB
2002
Springer
14 years 8 months ago
DNA sequence evolution with neighbor-dependent mutation
We introduce a model of DNA sequence evolution which can account for biases in mutation rates that depend on the identity of the neighboring bases. An analytic solution for this c...
Peter F. Arndt, Christopher B. Burge, Terence Hwa
SIGIR
2006
ACM
14 years 2 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
KDD
2000
ACM
211views Data Mining» more  KDD 2000»
14 years 3 days ago
Mining IC test data to optimize VLSI testing
We describe an application of data mining and decision analysis to the problem of die-level functional test in integrated circuit manufacturing. Integrated circuits are fabricated...
Tony Fountain, Thomas G. Dietterich, Bill Sudyka