1022 search results - page 101 / 205 » New models and algorithms for programmable networks |
100
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UAI
2003
15 years 2 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
117
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NIPS
2008
15 years 2 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
106
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CIAC
2003
Springer
15 years 6 months ago
2003
Springer
Abstract. We consider problems of (new) station placement along (existing) railway tracks, so as to increase the number of users. We prove that, in spite of the NP-hardness for the...
DATE
2002
IEEE
15 years 5 months ago
2002
IEEE
Microprocessors are today getting more and more inefficient for a growing range of applications. Its principles -The Von Neumann paradigm[3]- based on the sequential execution of ...
92
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ICPR
2010
IEEE
14 years 11 months ago
2010
IEEE
The quality of the lung nodule models determines the success of lung nodule detection. This paper describes aspects of our data-driven approach for modeling lung nodules using the...