Publication in fiscal year 2020 (Apr. 2020 – Mar. 2021)

Journal Paper

  1. C. Zhao, M. Ogura, and K. Sugimoto,
    “Stability optimization of positive semi-Markov jump linear systems via convex optimization,” SICE Journal of Control, Measurement, and System Integration, Vol. 13, No. 5, pp. 233-239, 2020.
  2. W. Mei, C. Zhao, M. Ogura, and K. Sugimoto,
    “Mixed H2/H∞ control for Markov jump linear systems with state and mode-observation delays,” IET Control Theory & Applications, Vol. 14, No. 15, pp.2076-2083, 2020.
  3. Kenta Hanada, Takayuki Wada, Izumi Masubuchi, Toru Asai, and Yasumasa Fujisaki,
    “Stochastic Consensus Algorithms over General Noisy Networks,” SICE Journal of Control, Measurement, and System Integration (accepted for publication), 2020.
  4. Taisuke Kobayashi,
    “q-VAE for Disentangled Representation Learning and Latent Dynamical Systems,” IEEE Robotics and Automation Letters, Vol. 5, No. 4, pp. 5669-5676, (2020)
  5. Taisuke Kobayashi and Toshiki Sugino,
    “Reinforcement Learning for Quadrupedal Locomotion with Design of Continual-Hierarchical Curriculum,” Engineering Applications of Artificial Intelligence, Vol. 95, pp. 103869, (2020)
  6. C. Zhao, M. Ogura, M. Kishida, and A. Yassine,
    “Optimal resource allocation for dynamic product development process via convex optimization”,
    Journal of Research in Engineering Design, (accepted for publication), (2020)
  7. S. Itadera, T. Kobayashi, J. Nakanishi, T. Aoyama, and Y. Hasegawa,
    “Towards Physical Interaction-based Sequential Mobility Assistance using Latent Generative Model of Movement State,” Advanced Robotics, (accepted for publication), (2020)
  8. T. Aotani, T. Kobayashi, and K. Sugimoto,
    “Bottom-up Multi-agent Reinforcement Learning by Reward Shaping for Cooperative-Competitive Tasks,” Applied Intelligence, (accepted for publication), (2020)
  9. W. E. L. Ilboudo, T. Kobayashi, and K. Sugimoto,
    “Robust Stochastic Gradient Descent with Student-t Distribution based First-order Momentum,” IEEE Transactions on Neural Networks and Learning Systems, (accepted for publication), (2020)

International Conference

  1. Kenta Hanada, Takayuki Wada, Izumi Masubuchi, Toru Asai, and Yasumasa Fujisaki,
    “Scaled Group Consensus over Weakly Connected Structurally Balanced Graphs”,
    21st IFAC World Congress, Berlin (1st Virtual IFAC World Congress), 2020.7.11-17 (Online).
  2. C. Zhao, M. Ogura, and K. Sugimoto,
    “”Finite-time control of discrete-time positive linear system via convex optimization,”
    SICE Annual Conference, 2020.9.23-26 (Online).
  3. Yuki Amemiya, Kenta Hanada, and Kenji Sugimoto,
    “An Asynchronous Heuristic Algorithm for Generalized Mutual Assignment Problem: Gossip-Based Approach,”
    The 52nd ISCIE International Symposium on Stochastic Systems Theory and Its Applications
    (SSS’20), Osaka University Convention Center, Osaka (Partially online)
    2020.10.29-30 (10.29).
  4. Kenji Sugimoto, Masaki Ogura, Kenta Hanada, and Toshitaka Aihara,
    “Sampled-data Suboptimal State Estimation over Lossy Networks,”
    The 52nd ISCIE International Symposium on Stochastic Systems Theory and Its Applications
    (SSS’20), Osaka University Convention Center, Osaka (Partially online)
    2020.10.29-30 (10.30).
  5. Kenji Sugimoto, Wataru Imahayashi, and Ryo Arimoto,
    “Relaxation of Strictly Positive Real Condition for Tuning Feedforward Control,”
    59th Conference on Decision and Control, Jeju Island, Republic of Korea
    (in a virtual format), 2020.11.14-18, to appear.

Press Release

Invited Talk