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» Process Modelling to Support Dependability Arguments
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NIPS
2004
15 years 1 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 6 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 3 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
14 years 11 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»
14 years 12 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...