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» Structure learning of Bayesian networks using constraints
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GPCE
2007
Springer
15 years 10 months ago
A type-centric framework for specifying heterogeneous, large-scale, component-oriented, architectures
Maintaining integrity, consistency, and enforcing conformance in architectures of large-scale systems requires specification and enforcement of many different forms of structural...
Georg Jung, John Hatcliff
AIED
2009
Springer
15 years 11 months ago
Detecting the Learning Value of Items In a Randomized Problem Set
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
Zachary A. Pardos, Neil T. Heffernan
CP
2009
Springer
16 years 5 months ago
Filtering Numerical CSPs Using Well-Constrained Subsystems
When interval methods handle systems of equations over the reals, two main types of filtering/contraction algorithms are used to reduce the search space. When the system is well-co...
Ignacio Araya, Gilles Trombettoni, Bertrand Neveu
CMOT
2004
141views more  CMOT 2004»
15 years 4 months ago
Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs
We describe a methodology to examine bipartite relational data structures as exemplified in networks of corporate interlocking. These structures can be represented as bipartite gr...
Garry Robins, Malcolm Alexander
INFOCOM
2005
IEEE
15 years 10 months ago
MV routing and capacity building in disruption tolerant networks
— Disruption-Tolerant networks (DTNs) differ from other types of networks in that capacity is exclusively created by the movements of participants. This implies that understandin...
Brendan Burns, Oliver Brock, Brian Neil Levine