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ICIP
2010
IEEE
15 years 1 months ago
Semi-supervised regression with temporal image sequences
We consider a semi-supervised regression setting where we have temporal sequences of partially labeled data, under the assumption that the labels should vary slowly along a sequen...
Ling Xie, Miguel Á. Carreira-Perpiñ&...
PODS
2007
ACM
122views Database» more  PODS 2007»
16 years 3 months ago
Privacy, accuracy, and consistency too: a holistic solution to contingency table release
The contingency table is a work horse of official statistics, the format of reported data for the US Census, Bureau of Labor Statistics, and the Internal Revenue Service. In many ...
Boaz Barak, Kamalika Chaudhuri, Cynthia Dwork, Sat...
IPMI
2001
Springer
16 years 4 months ago
Tracking Brain Deformations in Time-Sequences of 3D US Images
During a neurosurgical intervention, the brain tissues shift and warp. In order to keep an accurate positioning of the surgical instruments, one has to estimate this deformation f...
Xavier Pennec, Pascal Cachier, Nicholas Ayache
134
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RECOMB
2004
Springer
16 years 3 months ago
Finding approximate tandem repeats in genomic sequences
An efficient algorithm is presented for detecting approximate tandem repeats in genomic sequences. The algorithm is based on a flexible statistical model which allows a wide range...
Ydo Wexler, Zohar Yakhini, Yechezkel Kashi, Dan Ge...
MDAI
2007
Springer
15 years 9 months ago
Mining Frequent Diamond Episodes from Event Sequences
In this paper, we introduce a diamond episode of the form s1 → E → s2, where s1 and s2 are events and E is a set of events. The diamond episode s1 → E → s2 means that every...
Takashi Katoh, Kouichi Hirata, Masateru Harao