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Network-AI技術

  • 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.