Publications
2024
[IEEE Xplore] M. Zhao and M. Shimosaka, "Inverse Reinforcement Learning with Failed Demonstrations towards Stable Driving Behavior Modeling," 2024 IEEE Intelligent Vehicles Symposium (IV), Jeju Island, Korea, Republic of, 2024, pp. 2537-2544, doi: 10.1109/IV55156.2024.10588690.
oral presentation (top 5%)
2023
[poster presentation] M. Zhao, S. Yang, and M. Shimosaka. "Stabilization of Inverse Reinforcement Learning from Negative Data Focusing on Temporal Locality of High-risk Behaviors", 2023 JSME Conference on Robotics and Mechatronics (ROBOMECH).
2022
[IEEE Xplore] R. Furuhata, M. Zhao, K. Takahashi, Y. Shimomura and H. Takizawa, "Automated selection of build configuration based on machine learning," 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2022, pp. 934-941, doi: 10.1109/IPDPSW55747.2022.00151.
2021
[IEEE Xplore] M. Zhao, H. Takizawa and T. Soma, "Spatiotemporal Anomaly Detection for Large-Scale Sensor Data," 2021 12th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), 2021, pp. 162-168, doi: 10.1109/PAAP54281.2021.9720310.
2020
[IEEE Xplore] R. Furuhata, M. Zhao, M. Agung, R. Egawa and H. Takizawa, "Improving the Accuracy in SpMV Implementation Selection with Machine Learning," 2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW), 2020, pp. 172-177, doi: 10.1109/CANDARW51189.2020.00043.
[IEEE Xplore] M. Zhao, R. Furuhata, M. Agung, H. Takizawa and T. Soma, "Failure Prediction in Datacenters Using Unsupervised Multimodal Anomaly Detection," 2020 IEEE International Conference on Big Data (Big Data), 2020, pp. 3545-3549, doi: 10.1109/BigData50022.2020.9378419.
LHAM'20 Best workshop paper award