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Picture for Koji Yamamoto

Packet-Loss-Tolerant Split Inference for Delay-Sensitive Deep Learning in Lossy Wireless Networks


Apr 28, 2021
Sohei Itahara, Takayuki Nishio, Koji Yamamoto


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Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space


Apr 02, 2021
Akihito Taya, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto

* submitted to IEEE TSIPN 

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Zero-Shot Adaptation for mmWave Beam-Tracking on Overhead Messenger Wires through Robust Adversarial Reinforcement Learning


Feb 16, 2021
Masao Shinzaki, Yusuke Koda, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura, Yushi Shirato, Daisei Uchida, Naoki Kita

* 13 pages, 12 figures, 2 tables, under submission for possible publication for IEEE 

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Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data


Aug 14, 2020
Sohei Itahara, Takayuki Nishio, Yusuke Koda, Masahiro Morikura, Koji Yamamoto


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Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning


Apr 21, 2020
Sohei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto


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Hybrid-FL: Cooperative Learning Mechanism Using Non-IID Data in Wireless Networks


May 17, 2019
Naoya Yoshida, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto, Ryo Yonetani


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Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs with Graph Convolutional Networks


May 17, 2019
Kota Nakashima, Shotaro Kamiya, Kazuki Ohtsu, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura


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