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» The Complexity of Distributions
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JMLR
2010
202views more  JMLR 2010»
15 years 1 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
IJSEKE
2011
141views more  IJSEKE 2011»
14 years 10 months ago
Risk Assessment in Multi-disciplinary (Software+) Engineering Projects
Software systems in safety-critical industrial automation systems, such as power plants and steel mills, become increasingly large, complex, and distributed. For assessing risks, l...
Stefan Biffl, Thomas Moser, Dietmar Winkler
NLDB
2011
Springer
14 years 9 months ago
Querying Linked Data Using Semantic Relatedness: A Vocabulary Independent Approach
Abstract. Linked Data brings the promise of incorporating a new dimension to the Web where the availability of Web-scale data can determine a paradigmatic transformation of the Web...
André Freitas, João Gabriel Oliveira...
HPDC
2010
IEEE
15 years 7 months ago
Characterising a grid site's traffic
Grid computing has been widely adopted for intensive high performance computing. Since grid resources are distributed over complex large-scale infrastructures, understanding grid ...
Tiejun Ma, Yehia El-khatib, Michael Mackay, Christ...
PODC
2010
ACM
15 years 10 months ago
Eventually linearizable shared objects
Linearizability is the strongest known consistency property of shared objects. In asynchronous message passing systems, Linearizability can be achieved with 3S and a majority of c...
Marco Serafini, Dan Dobre, Matthias Majuntke, P&ea...