| Client selection for federated learning with heterogeneous resources in mobile edge T Nishio, R Yonetani ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-7, 2019 | 257 | 2019 |
| Service-oriented heterogeneous resource sharing for optimizing service latency in mobile cloud T Nishio, R Shinkuma, T Takahashi, NB Mandayam Proceedings of the first international workshop on Mobile cloud computing …, 2013 | 174 | 2013 |
| Adaptive resource discovery in mobile cloud computing W Liu, T Nishio, R Shinkuma, T Takahashi Computer Communications 50, 119-129, 2014 | 52 | 2014 |
| Hybrid-FL for wireless networks: Cooperative learning mechanism using non-IID data N Yoshida, T Nishio, M Morikura, K Yamamoto, R Yonetani ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-7, 2020 | 32* | 2020 |
| Extreme URLLC: Vision, challenges, and key enablers J Park, S Samarakoon, H Shiri, MK Abdel-Aziz, T Nishio, A Elgabli, ... arXiv preprint arXiv:2001.09683, 2020 | 31 | 2020 |
| Proactive received power prediction using machine learning and depth images for mmWave networks T Nishio, H Okamoto, K Nakashima, Y Koda, K Yamamoto, M Morikura, ... IEEE Journal on Selected Areas in Communications 37 (11), 2413-2427, 2019 | 25 | 2019 |
| Proactive base station selection based on human blockage prediction using RGB-D cameras for mmWave communications Y Oguma, R Arai, T Nishio, K Yamamoto, M Morikura 2015 IEEE Global Communications Conference (GLOBECOM), 1-6, 2015 | 22 | 2015 |
| Proactive handover based on human blockage prediction using RGB-D cameras for mmWave communications Y Oguma, T Nishio, K Yamamoto, M Morikura IEICE Transactions on Communications 99 (8), 1734-1744, 2016 | 18 | 2016 |
| Machine-learning-based throughput estimation using images for mmWave communications H Okamoto, T Nishio, M Morikura, K Yamamoto, D Murayama, K Nakahira 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 1-6, 2017 | 17 | 2017 |
| Experimental investigation of co-channel and adjacent channel operations of microwave power and IEEE 802.11 g data transmissions N Imoto, S Yamashita, T Ichihara, K Yamamoto, T Nishio, M Morikura, ... IEICE Transactions on Communications 97 (9), 1835-1842, 2014 | 17 | 2014 |
| Recurrent neural network-based received signal strength estimation using depth images for mmWave communications H Okamoto, T Nishio, M Morikura, K Yamamoto 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC …, 2018 | 14 | 2018 |
| Handover management for mmwave networks with proactive performance prediction using camera images and deep reinforcement learning Y Koda, K Nakashima, K Yamamoto, T Nishio, M Morikura IEEE Transactions on Cognitive Communications and Networking 6 (2), 802-816, 2019 | 13* | 2019 |
| Reinforcement learning based predictive handover for pedestrian-aware mmWave networks Y Koda, K Yamamoto, T Nishio, M Morikura IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops …, 2018 | 13 | 2018 |
| Novel coexistence scheme between wireless sensor network and wireless LAN for HEMS F Inoue, M Morikura, T Nishio, K Yamamoto, F Nuno, T Sugiyama 2013 IEEE International Conference on Smart Grid Communications …, 2013 | 12 | 2013 |
| Analysis of inversely proportional carrier sense threshold and transmission power setting K Yamamoto, X Yang, T Nishio, M Morikura, H Abeysekera 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC …, 2017 | 11 | 2017 |
| Proactive traffic control based on human blockage prediction using RGBD cameras for millimeter-wave communications T Nishio, R Arai, K Yamamoto, M Morikura 2015 12th Annual IEEE Consumer Communications and Networking Conference …, 2015 | 11* | 2015 |
| Implementation and feasibility study of co-channel operation system of microwave power transmissions to IEEE 802.11-based batteryless sensor S Yamashita, N Imoto, T Ichihara, K Yamamoto, T Nishio, M Morikura, ... IEICE Transactions on Communications 97 (9), 1843-1852, 2014 | 11 | 2014 |
| Deep reinforcement learning-based channel allocation for wireless lans with graph convolutional networks K Nakashima, S Kamiya, K Ohtsu, K Yamamoto, T Nishio, M Morikura IEEE Access 8, 31823-31834, 2020 | 10 | 2020 |
| Measurement method of temporal attenuation by human body in off-the-shelf 60 GHz WLAN with HMM-based transmission state estimation Y Koda, K Yamamoto, T Nishio, M Morikura Wireless Communications and Mobile Computing 2018, 2018 | 10 | 2018 |
| Knowledge-based reestablishment of primary exclusive region in database-driven spectrum sharing S Yamashita, K Yamamoto, T Nishio, M Morikura IEICE Transactions on Communications 99 (9), 2019-2027, 2016 | 9 | 2016 |
Koji YamamotoGraduate School of Informatics, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
