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» Deterministic Sampling Algorithms for Network Design
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BMCBI
2010
167views more  BMCBI 2010»
14 years 9 months ago
Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach
Background: Transcriptional gene regulation is one of the most important mechanisms in controlling many essential cellular processes, including cell development, cell-cycle contro...
Marc Bailly-Bechet, Alfredo Braunstein, Andrea Pag...
CORR
2010
Springer
94views Education» more  CORR 2010»
14 years 9 months ago
Real-Time Multi-path Tracking of Probabilistic Available Bandwidth
Applications such as traffic engineering and network provisioning can greatly benefit from knowing, in real time, what is the largest input rate at which it is possible to transmit...
Frederic Thouin, Mark Coates, Michael Rabbat
GLOBECOM
2008
IEEE
15 years 3 months ago
GLRT-Based Spectrum Sensing for Cognitive Radio
—In this paper, we propose several spectrum sensing methods designed using the generalized likelihood ratio test (GLRT) paradigm, for application in a cognitive radio network. Th...
Teng Joon Lim, Rui Zhang, Ying-Chang Liang, Yongho...
DAC
2005
ACM
14 years 11 months ago
Power grid simulation via efficient sampling-based sensitivity analysis and hierarchical symbolic relaxation
On-chip supply networks are playing an increasingly important role for modern nanometer-scale designs. However, the ever growing sizes of power grids make the analysis problem ext...
Peng Li
79
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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 1 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard