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» Set cover algorithms for very large datasets
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CVPR
2008
IEEE
15 years 11 months ago
An efficient algorithm for compressed MR imaging using total variation and wavelets
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
15 years 2 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
ICCCN
2008
IEEE
15 years 4 months ago
p-Percent Coverage Schedule in Wireless Sensor Networks
—We investigate the p-percent coverage problem in this paper and propose two algorithms to prolong network lifetime based on the fact that for some applications full coverage is ...
Shan Gao, Xiaoming Wang, Yingshu Li
BMCBI
2010
173views more  BMCBI 2010»
14 years 10 months ago
The Yeast Resource Center Public Image Repository: A large database of fluorescence microscopy images
Background: There is increasing interest in the development of computational methods to analyze fluorescent microscopy images and enable automated large-scale analysis of the subc...
Michael Riffle, Trisha N. Davis
BMCBI
2008
186views more  BMCBI 2008»
14 years 10 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells