A. Suzuki, R. Kawahara and S. Harada, "Cooperative Multi-Agent Deep Reinforcement Learning for Dynamic Virtual Network Allocation," ICCCN 2021, July 2021.
K. Tajiri, T. Iwata, Y. Matsuo and K. Watanabe, "Fault Detection of ICT systems with Deep Learning Model for Missing Data, " 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM), 2021, pp. 445-451
H. Ikeuchi, Y. Takahashi, K. Matsuda and T. Toyono, "Recovery Process Visualization based on Automaton Construction," 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM), 2021, pp. 10-18.
Y. Matsuo, T. Kimura, K. Nishimatsu, "DeepSIP: A System for Predicting Service Impact of Network Failure by Temporal Multimodal CNN", IEICE Transactions on Information and Systems, Vol.E104-B, No.10, 2021.
Y. Hashimoto, I. Ishikawa, M. Ikeda, Y. Matsuo, and Y. Kawahara, "Krylov subspace method for nonlinear dynamical systems with random noise ," JMLR, 21, 172: 1-29, 2020.
A. Suzuki, R. Kawahara, M. Kobayashi, Y. Takahashi, S. Harada, and K. Ishibashi, "Extendable NFV-Integrated Control Method Using Reinforcement Learning," IEICE Transactions on Communications, Vol. E103.B, No. 8, pp. 826-841, 2020.
A. Suzuki and S. Harada, "Safe Multi-Agent Deep Reinforcement Learning for Dynamic Virtual Network Allocation," IEEE GLOBECOM 2020, Dec. 2020.
H. Ikeuchi, A. Watanabe, T. Hirao, M. Morishita, M. Nishino, Y. Matsuo and K. Watanabe, "Recovery command generation towards automatic recovery in ICT systems by Seq2Seq learning," Proc. IEEE/IFIP, NOMS 2020(mini-conf), 2020.
K. Tajiri, Y. Ikeda, Y. Nakano, and K. Watanabe, "Dividing Deep Learning Model for Continuous Anomaly Detection of Inconsistent ICT Systems," IEEE/IFIP Network Operations and Management Symposium, 2020.
Y. Matsuo, T. Kimura and K. Nishimatsu, "DeepSIP: A System for Predicting Service Impact of Network Failure by Temporal Multimodal CNN," Proc. IEEE/IFIP AnNet, 2020.
Y.Ikeda, K. Ishibashi, Y. Nakano, K. Watanabe, K. Tajiri, and R. Kawahara, “Human-Assisted Online Anomaly Detection with Normal Outlier Retraining,” ACM SIGKDD 2018 Workshop ODD v5.0, Aug. 2018.
Y. Ikeda, K. Ishibashi, Y. Nakano, K. Watanabe, R. Kawahara, "Anomaly Detection and Interpretation using Multimodal Autoencoder and Sparse Optimization," arXiv preprint arXiv:1812.07136, 2018.
Y. Matsuo, Y. Nakano, A. Watanabe, K. Watanabe, K. Ishibashi, and K. Kawahara, “Root-cause diagnosis for rare failures using Bayesian network with dynamic modification,” Proc. IEEE, ICC, 2018.
Y.Ikeda, K. Tajiri, Y. Nakano, K. Watanabe, K. Ishibashi,“Unsupervised Estimation of Dimensions Contributing to Detected Anomalies with Variational Autoencoders,”AAAI-19 Workshop on Network Interpretability for Deep Learning, 2019.