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Takayuki Nishio
Takayuki Nishio
School of Engineering, Tokyo Tech
Verified email at ict.e.titech.ac.jp - Homepage
Title
Cited by
Cited by
Year
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
6612019
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
1942013
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
91*2020
Extreme ultra-reliable and low-latency communication
J Park, S Samarakoon, H Shiri, MK Abdel-Aziz, T Nishio, A Elgabli, ...
Nature Electronics 5 (3), 133-141, 2022
70*2022
Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
S Itahara, T Nishio, Y Koda, M Morikura, K Yamamoto
IEEE Transactions on Mobile Computing, 2021
582021
Adaptive resource discovery in mobile cloud computing
W Liu, T Nishio, R Shinkuma, T Takahashi
Computer Communications 50, 119-129, 2014
552014
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
482019
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
332020
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
332019
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
282018
Differentially private aircomp federated learning with power adaptation harnessing receiver noise
Y Koda, K Yamamoto, T Nishio, M Morikura
GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-6, 2020
272020
Communication-efficient multimodal split learning for mmWave received power prediction
Y Koda, J Park, M Bennis, K Yamamoto, T Nishio, M Morikura, ...
IEEE Communications Letters 24 (6), 1284-1288, 2020
242020
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
242017
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
242015
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
232016
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
182014
MAB-based Client Selection for Federated Learning with Uncertain Resources in Mobile Networks
N Yoshida, T Nishio, M Morikura, K Yamamoto
IEEE GLOBECOM Wksp on OpenMLC, 2020
152020
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
152018
Data assessment and prioritization in mobile networks for real-time prediction of spatial information with machine learning
R Shinkuma, T Nishio
2019 IEEE First International Workshop on Network Meets Intelligent …, 2019
142019
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
122017
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