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» Every Sequence Is Decompressible from a Random One
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BMCBI
2008
101views more  BMCBI 2008»
14 years 11 months ago
Prediction of glycosylation sites using random forests
Background: Post translational modifications (PTMs) occur in the vast majority of proteins and are essential for function. Prediction of the sequence location of PTMs enhances the...
Stephen E. Hamby, Jonathan D. Hirst
CSIE
2009
IEEE
15 years 5 months ago
Identifying DNA Strands Using a Kernel of Classified Sequences
— Automated DNA sequencing produces a large amount of raw DNA sequence data that then needs to be classified, organized, and annotation. One major application is the comparison o...
Guillermo Tonsmann, David D. Pollock, Wanjun Gu, T...
COCO
2009
Springer
155views Algorithms» more  COCO 2009»
15 years 5 months ago
Weak Derandomization of Weak Algorithms: Explicit Versions of Yao's Lemma
—A simple averaging argument shows that given a randomized algorithm A and a function f such that for every input x, Pr[A(x) = f(x)] ≥ 1−ρ (where the probability is over the...
Ronen Shaltiel
IJCV
2006
159views more  IJCV 2006»
14 years 11 months ago
Wide Baseline Matching between Unsynchronized Video Sequences
3D reconstruction of a dynamic scene from features in two cameras usually requires synchronization and correspondences between the cameras. These may be hard to achieve due to occl...
Lior Wolf, Assaf Zomet
ECCV
2008
Springer
16 years 26 days ago
A Dynamic Conditional Random Field Model for Joint Labeling of Object and Scene Classes
Object detection and pixel-wise scene labeling have both been active research areas in recent years and impressive results have been reported for both tasks separately. The integra...
Christian Wojek, Bernt Schiele