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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
RISING
(3rd)		 2023-10-31
14:00		 Hokkaido Kaderu 2・7 (Sapporo) [Poster Presentation] Optimal Compression Rate for Multiple Data Compression Techniques in Data Parallel Distributed Deep Learning
Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) 		In distributed deep learning, where multiple processors are used, the learning time can be significantly reduced by exec... [more]
NS 2023-10-05
10:10		 Hokkaido Hokkaidou University + Online
(Primary: On-site, Secondary: Online)		 [Encouragement Talk] Communication Scheduling Based on Heuristic Algorithm in Distributed Deep Learning
Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) NS2023-86		 In distributed deep learning, where multiple processors are used, the learning time can be significantly reduced by exec... [more] NS2023-86
pp.83-88
NS, ICM, CQ, NV
(Joint)		 2022-11-24
13:00		 Fukuoka Humanities and Social Sciences Center, Fukuoka Univ. + Online
(Primary: On-site, Secondary: Online)		 Optimal Data Communication Scheduling Considering Multiple Data Compression Techniques in Distributed Deep Learning
Fukuda Ryudai, Takuji Tachibana (Univ. Fukui) NS2022-105		 In distributed deep learning, which uses multiple processors, the training time can be greatly reduced by executing the ... [more] NS2022-105
pp.29-34
RISING
(3rd)		 2021-11-16
09:30		 Tokyo
(Primary: On-site, Secondary: Online)		 Optimal Data Communication Scheduling Considering Multiple Data Compression Techniques in Distributed Deep Learning
Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) 		 [more]
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