Suitable is the best: Least absolute deviation algorithm under high-mobility non-Gaussian noise environments
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: 2014شناسه الکترونیک: 10.1109/IPDPS.2014.59
کلیدواژه(گان): learning (artificial intelligence),n program compilers,n software libraries,n sorting,n Nitro,n adaptive code variant tuning framework,n autotuning systems,n graph computations,n irregular GPU benchmarks,n library interface,n machine learning,n meta-information,n optimization criteria,n overhead reduction,n programmer-directed autotuning framework,n search space navigation,n sorting,n sparse numerical methods,n training time reduction,n Li
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Suitable is the best: Least absolute deviation algorithm under high-mobility non-Gaussian noise environments
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| contributor author | Gui, Guan | |
| contributor author | Li Xu | |
| contributor author | Adachi, Fumiyuki | |
| date accessioned | 2020-03-12T22:16:07Z | |
| date available | 2020-03-12T22:16:07Z | |
| date issued | 2014 | |
| identifier other | 7000208.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1077078 | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Suitable is the best: Least absolute deviation algorithm under high-mobility non-Gaussian noise environments | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8213316 | |
| subject keywords | learning (artificial intelligence) | |
| subject keywords | n program compilers | |
| subject keywords | n software libraries | |
| subject keywords | n sorting | |
| subject keywords | n Nitro | |
| subject keywords | n adaptive code variant tuning framework | |
| subject keywords | n autotuning systems | |
| subject keywords | n graph computations | |
| subject keywords | n irregular GPU benchmarks | |
| subject keywords | n library interface | |
| subject keywords | n machine learning | |
| subject keywords | n meta-information | |
| subject keywords | n optimization criteria | |
| subject keywords | n overhead reduction | |
| subject keywords | n programmer-directed autotuning framework | |
| subject keywords | n search space navigation | |
| subject keywords | n sorting | |
| subject keywords | n sparse numerical methods | |
| subject keywords | n training time reduction | |
| subject keywords | n Li | |
| identifier doi | 10.1109/IPDPS.2014.59 | |
| journal title | igh Mobility Wireless Communications (HMWC), 2014 International Workshop on | |
| filesize | 916454 | |
| citations | 0 |