15 citations · 46 across the 10 of their papers we have counts for
19 papers
Packet-Loss-Tolerant Split Inference for Delay-Sensitive Deep Learning in Lossy Wireless Networks
Sohei Itahara, Takayuki Nishio, Koji Yamamoto
The distributed inference framework is an emerging technology for real-time applications empowered by cutting-edge deep machine learning (ML) on resource-constrained Internet of th…
Zero-Shot Adaptation for mmWave Beam-Tracking on Overhead Messenger Wires through Robust Adversarial Reinforcement Learning
Masao Shinzaki, Yusuke Koda, Koji Yamamoto +5
Millimeter wave (mmWave) beam-tracking based on machine learning enables the development of accurate tracking policies while obviating the need to periodically solve beam-optimizat…
Millimeter Wave Communications on Overhead Messenger Wire: Deep Reinforcement Learning-Based Predictive Beam Tracking
Yusuke Koda, Masao Shinzaki, Koji Yamamoto +5
This paper discusses the feasibility of beam tracking against dynamics in millimeter wave (mmWave) nodes placed on overhead messenger wires, including wind-forced perturbations and…
MAB-based Client Selection for Federated Learning with Uncertain Resources in Mobile Networks
Naoya Yoshida, Takayuki Nishio, Masahiro Morikura +1
This paper proposes a client selection method for federated learning (FL) when the computation and communication resource of clients cannot be estimated; the method trains a machin…
Distributed Heteromodal Split Learning for Vision Aided mmWave Received Power Prediction
Yusuke Koda, Jihong Park, Mehdi Bennis +3
The goal of this work is the accurate prediction of millimeter-wave received power leveraging both radio frequency (RF) signals and heterogeneous visual data from multiple distribu…
Transfer Learning-Based Received Power Prediction with Ray-tracing Simulation and Small Amount of Measurement Data
Masahiro Iwasaki, Takayuki Nishio, Masahiro Morikura +1
This paper proposes a method to predict received power in urban area deterministically, which can learn a prediction model from small amount of measurement data by a simulation-aid…