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» Process Modelling to Support Dependability Arguments
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NIPS
2004
15 years 3 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
CORR
2010
Springer
122views Education» more  CORR 2010»
14 years 9 months ago
Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavio...
Guangyue Han, Brian H. Marcus
CASES
2007
ACM
15 years 6 months ago
A fast and generic hybrid simulation approach using C virtual machine
Instruction Set Simulators (ISSes) are important tools for cross-platform software development. The simulation speed is a major concern and many approaches have been proposed to i...
Lei Gao, Stefan Kraemer, Rainer Leupers, Gerd Asch...
CAD
2002
Springer
15 years 2 months ago
Sharing Product Data among Heterogeneous Workflow Environments
Nowadays, we increasingly face the situation that possibly heterogeneous workflow environments must be integrated in order to support company-internal business processes as well a...
Markus Bon, Norbert Ritter, Theo Härder
BMCBI
2010
109views more  BMCBI 2010»
15 years 2 months ago
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...