Presentation | 2003/7/22 Predicting Internet Packet Transmission Delay via Sequential Monte Carlo Kensaku WADA, Takayuki KURIHARA, Takashi MATSUMOTO, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Packet transmission delay is one of the important quantities associated with Internet. Predictions of Internet packet delay is far from trivial for many reasons. This paper attempts to formulate the packet transmission delay predictions using Bayesian Sequential Monte Carlo, which learns data in a sequential manner, and makes predictions online. A preliminary experimental result is reported. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Bayes / Online learning / Internet Packet transmission Deray / Sequential Monte Carlo |
Paper # | NC2003-37 |
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Committee | NC |
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Conference Date | 2003/7/22(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Predicting Internet Packet Transmission Delay via Sequential Monte Carlo |
Sub Title (in English) | |
Keyword(1) | Bayes |
Keyword(2) | Online learning |
Keyword(3) | Internet Packet transmission Deray |
Keyword(4) | Sequential Monte Carlo |
1st Author's Name | Kensaku WADA |
1st Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University() |
2nd Author's Name | Takayuki KURIHARA |
2nd Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University |
3rd Author's Name | Takashi MATSUMOTO |
3rd Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University:CREST |
Date | 2003/7/22 |
Paper # | NC2003-37 |
Volume (vol) | vol.103 |
Number (no) | 228 |
Page | pp.pp.- |
#Pages | 5 |
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