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
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...
—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 ...
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...
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...