| 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, 2020 | 198 | 2020 |
| Packet-Loss-Tolerant Split Inference for Delay-Sensitive Deep Learning in Lossy Wireless Networks S Itahara, T Nishio, K Yamamoto IEEE GLOBECOM 2021, 2021 | 16 | 2021 |
| Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning S Itahara, T Nishio, M Morikura, K Yamamoto IEEE VTC Fall 2020, 1-6, 2020 | 12 | 2020 |
| Communication-oriented Model Fine-tuning for Packet-loss Resilient Distributed Inference under Highly Lossy IoT Networks S Itahara, T Nishio, Y Koda, K Yamamoto IEEE Access 10, 14969 - 14979, 2022 | 9 | 2022 |
| Beamforming feedback-based model-driven angle of departure estimation toward legacy support in WiFi sensing: An experimental study S Itahara, S Kondo, K Yamashita, T Nishio, K Yamamoto, Y Koda IEEE Access 10, 59737-59747, 2022 | 6 | 2022 |
| Bi-directional beamforming feedback-based firmware-agnostic WiFi sensing: An empirical study S Kondo, S Itahara, K Yamashita, K Yamamoto, Y Koda, T Nishio, A Taya IEEE Access 10, 36924-36934, 2022 | 5 | 2022 |
| Watch from sky: machine-learning-based multi-UAV network for predictive police surveillance R Sugano, R Shinkuma, T Nishio, NB Mandayam 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC), 656-657, 2023 | 3 | 2023 |
| Frame-Capture-Based CSI Recomposition Pertaining to Firmware-Agnostic WiFi Sensing R Hanahara, S Itahara, K Yamashita, Y Koda, A Taya, T Nishio, ... IEEE CCNC, 1-6, 2022 | 2 | 2022 |
| Bi-directional Beamforming Feedback-based Firmware-agnostic WiFi Sensing. S Kondo, S Itahara, K Yamashita, K Yamamoto, Y Koda, T Nishio, A Taya arXiv preprint arXiv:2112.06695, 2021 | 1 | 2021 |
| Computer vision-assisted single-antenna and single-anchor RSSI localization harnessing dynamic blockage events T Sunami, S Itahara, Y Koda, T Nishio, K Yamamoto arXiv preprint arXiv:2107.04770, 2021 | 1 | 2021 |
| Online Trainable Wireless Link Quality Prediction System using Camera Imagery S Itahara, T Nishio, M Morikura, K Yamamoto IEEE GLOBECOM Wksp on OpenMLC, 1-6, 2020 | 1 | 2020 |
| A Study for Knowlage Distillation Based Semi-Supervised Federated Learning with Low Communication Cost S Itahara, T Nishio, M Morikura, K Yamamoto IEICE Technical Report; IEICE Tech. Rep., 2019 | 1 | 2019 |
| Always-Connected Enablement Base Station to eliminate the effects of RRC transitions delay T Ogawara, K Okonogi, A Suzuki, M Kurata, S Itahara, T Nagano, ... 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall), 1-5, 2023 | | 2023 |
| MAB-based Joint Optimization of Wireless LAN and Machine Learning for Communication-efficient Distributed Inference in Lossy Networks K Yorita, S Itahara, T Nishio, D Yoda, T Nabetani 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), 1-5, 2022 | | 2022 |
| A Study of Beamforming Feedback-based Model-driven Angle of Departure Estimation S Itahara, T Nishio, K Yamamoto IEICE Technical Report; IEICE Tech. Rep. 121 (333), 59-61, 2022 | | 2022 |
| A Study of Computer Vision-aided Single-antenna and Single-anchor RSSI Localization Considering Movable Obstructions T Sunami, S Itahara, Y Koda, T Nishio, K Yamamoto IEICE Technical Report; IEICE Tech. Rep. 121 (333), 89-91, 2022 | | 2022 |
| Evaluation of Few Round Training with Distillation-Based Semi-Supervised Federated Learning Y Yoshida, S Itahara, T Nishio IEICE Technical Report; IEICE Tech. Rep. 121 (333), 48-50, 2022 | | 2022 |
| A Study of Online Training Method for Image-based Wireless Link Quality Prediction S Itahara, T Nishio, M Morikura, K Yamamoto IEICE Technical Report; IEICE Tech. Rep. 120 (315), 7-9, 2021 | | 2021 |
| Computer Vision-assisted Decimeter-level Single-antenna RSSI Localization Harnessing Dynamic Blockage Events. T Sunami, S Itahara, Y Koda, T Nishio, K Yamamoto CoRR, 2021 | | 2021 |
| A Study of Joint Control of Machine Learning Model and Wireless LAN Parameters in Split inference by Reinforcement Learning K Yorita, S Itahara, T Nishio, D Yoda, T Nabetani IEICE Technical Report; IEICE Tech. Rep., 0 | | |
