An analytical approach to study cascading failures in finite-size random geometric networks
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: 2014DOI: 10.1109/CVPR.2014.128
Keyword(s): Approximation methods,n Graphical models,n Kernel,n Linear programming,n Optimization,n Training,n Vectors,n Beta process,n classification,n instance selection,n multiple kernel learning,n variational inference
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An analytical approach to study cascading failures in finite-size random geometric networks
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| contributor author | Eslami, Ali | |
| contributor author | Huang, Chuan | |
| contributor author | Zhang, Junshan | |
| contributor author | Cui, Shuguang | |
| date accessioned | 2020-03-12T22:53:51Z | |
| date available | 2020-03-12T22:53:51Z | |
| date issued | 2014 | |
| identifier other | 7028580.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1098363 | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | An analytical approach to study cascading failures in finite-size random geometric networks | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8239550 | |
| subject keywords | Approximation methods | |
| subject keywords | n Graphical models | |
| subject keywords | n Kernel | |
| subject keywords | n Linear programming | |
| subject keywords | n Optimization | |
| subject keywords | n Training | |
| subject keywords | n Vectors | |
| subject keywords | n Beta process | |
| subject keywords | n classification | |
| subject keywords | n instance selection | |
| subject keywords | n multiple kernel learning | |
| subject keywords | n variational inference | |
| identifier doi | 10.1109/CVPR.2014.128 | |
| journal title | ommunication, Control, and Computing (Allerton), 2014 52nd Annual Allerton Conference on | |
| filesize | 773693 | |
| citations | 0 |