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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
(2nd)		 2019-11-27
13:55		 Tokyo Fukutake Learning Theater, Hongo Campus, Univ. Tokyo [Poster Presentation] Handover Control for mmWave Networks with Proactive Performance Prediction Using Depth Images and Deep Reinforcement Learning
Yusuke Koda, Kota Nakashima, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.) 		 [more]
MIKA
(2nd)		 2019-10-03
11:15		 Hokkaido Hokkaido Univ. [Poster Presentation] Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs -- Investigation of sampling method of replay buffer --
Kota Nakashima, Shotaro Kamiya, Ohtsu Kazuki, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.) 		We have proposed the deep reinforcement learning-based channel allocation approach for wireless area local networks to i... [more]
RCS 2019-06-19
15:25		 Okinawa Miyakojima Hirara Port Terminal Building Optimal Path Learning for mmWave Communications in Smart Factory
Mayu Mieda, Shotaro Kamiya, Kota Nakashima, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.) RCS2019-55		  [more] RCS2019-55
pp.109-112
ASN 2019-01-28
14:40		 Kagoshima Kyuukamura Ibusuki Deep Reinforcement Learning-Based Optimum Channel Control for Wireless LAN
Kota Nakashima, Syotaro Kamiya, Kazuki Ohtsu, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.) ASN2018-80		 This report proposes deep reinforcement learning-based channel selection method when access points (APs) are located den... [more] ASN2018-80
pp.13-18
ASN, NS, RCS, SR, RCC
(Joint)		 2018-07-12
10:55		 Hokkaido Hakodate Arena [Poster Presentation] Deep Learning Based RSS Prediction Using RGB-D Camera for mmWave Communications
Kota Nakashima, Yusuke Koda, Koji Yamamoto, Hironao Okamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.) RCC2018-37 NS2018-50 RCS2018-95 SR2018-34 ASN2018-31		 This paper experimentally finds the optimum number of input images of a machine learning-based mmWave received signal st... [more] RCC2018-37 NS2018-50 RCS2018-95 SR2018-34 ASN2018-31
pp.75-76(RCC), pp.81-82(NS), pp.93-94(RCS), pp.85-86(SR), pp.91-92(ASN)
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