研究業績

2018年

査読付き論文

• T. Wazawa, Y. Arai, Y. Kawahara, H. Takauchi, T. Washio & T. Nagai, "Highly biocompatible super-resolution fluorescence imaging using the fast photoswitching fluorescent protein Kohinoor and SPoD-ExPAN with Lp-regularized image reconstruction," Microscopy (in press).

2017年

査読付き論文

• N. Takeishi, Y. Kawahara & T. Yairi, "Learning Koopman invariant subspaces for dynamic mode decomposition," in Advances in Neural Information Processing Systems 30 (Proc. of NIPS’17), pp.1130-1140, 2017 [Code].
• H. Tanabe, K. Fujii & M. Kouzaki, "Intermittent muscle activity in the feedback loop of postural control system during natural quiet standing," Scientific Reports, Vol.7, 10631, 2017.
• N. Takeishi, Y. Kawahara & T. Yairi, "Subspace dynamic mode decomposition for stochastic Koopman analysis," Physical Review E, Vol.96, 03310, 2017.
• K. Fujii, Y. Inaba & Y. Kawahara, "Koopman spectral kernels for comparing complex dynamics: Application to multiagent sport plays," in Proc. of the 2017 European Conf. on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'17), pp.127-139, 2017.
• K. Takeuchi, Y. Kawahara & T. Iwata, "Structurally regularized non-negative tensor factorization for spatio-temporal pattern discoveries," in Proc. of the 2017 European Conf. on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'17), pp.582-598, 2017.
• K. Fujii, Y. Yoshihara, H. Tanabe & Y. Yamamoto, "Switching adaptability in human-inspired sidesteps: A minimal model," Frontiers in Human Neuroscience, Vol.11, 298, 2017.
• N. Takeishi, Y. Kawahara & T. Yairi, "Sparse non-negative dynamic mode decomposition," in Proc. of the 2017 IEEE Int'l Conf. on Image Processing (ICIP'17), pp.2682-2686, 2017.
• N. Takeishi, Y. Kawahara, Y. Tabei & T. Yairi, "Bayesian dynamic mode decomposition," in Proc. of the 26th Int'l Joint Conf. on Artificial Intelligence (IJCAI'17), pp.2814-2821, 2017 [Code].
• D. Yamashita, K. Fujii, S. Yoshioka & T. Isaka, M. Kouzaki, "Asymmetric interlimb role-sharing in mechanical power during human sideways locomotion," Journal of Biomechanics, vol.57, pp.79-86, 2017.
• Y. Hasegawa, K. Fujii, A. Miura & Y. Yamamoto, "Resolution of low-velocity control in golf putting differentiates professionals from amateurs," Journal of Sports Sciences, vol.35, No.13, 1239-1246, 2017.
• H. Tanabe, K. Fujii & M. Kouzaki, "Joint coordination and muscle activities of ballet dancers during tiptoe standing," Motor Control, vol.21, No.1, 72-89, 2017.
• H. Wang, Y. Kawahara, C. Weng & J. Yuan, "Representative selection with structured sparsity," Pattern Recognition, Vol.63, pp.268–278, 2017.

招待講演

• Y. Kawahara, "Nonparametric Bayesian learning of Koopman spectrums in nonlinear dynamical systems," The 2017 Int'l Symp. on Nonlinear Theory and Its Applications (NOLTA'17), Cancún, Mexico, 2017年12月.
• 河原吉伸, "機械学習を用いたデータからのダイナミクス抽出: クープマン解析に関連する話題を中心として," SICE-DML, 2017年9月.
• Y. Kawahara, "Data-driven modeling of dynamical systems," Osaka CTSR - RIKEN iTHES/iTHEMS - Kali IPMU Joint Symposium, Osaka, Japan, June, 2017.
• Y. Kawahara, "Koopman spectral learning of dynamical systems," UK-Japan AI Research Workshop, Tokyo, Japan, 2017年3月.
• 河原吉伸, "劣モジュラ性を用いた機械学習〜適応的劣モジュラ性を中心として," 計測制御自動学会SI部門ロボットマニピュレーションに関する技術調査研究会主催定例講演会, 大阪, 2017年3月.

その他の論文、発表など

• 河原吉伸, "構造的学習", 人工知能学大事典, pp.432-434, 共立出版, 2017年7月.
• 河原吉伸, "劣モジュラ最適化と機械学習," 人工知能学大事典, pp.506-508, 共立出版, 2017年7月.
• 藤井慶輔, 河原吉伸, 稲葉優希, 元安陽一, 山本裕二, "集団スポーツの位置情報データを用いた機械学習による複数人協力プレーの識別," 第31回人工知能学会全国大会, 2O1-4, 名古屋, 2017年5月.
• 武石直也, 河原吉伸, 矢入健久, "ベイズ的動的モード分解," 第31回人工知能学会全国大会, 4I2-4, 名古屋, 2017年5月.
• 安藤雅行, 河原吉伸, 砂山渡, 畑中裕司, 小郷原一智, "ディープラーニングにおける分類パターンの意味付け支援," 第31回人工知能学会全国大会, 2M2-OS-34a-2, 名古屋, 2017年5月.
• 和沢鉄一, 新井由之, 河原吉伸, 中野雅裕, 松田知己, 鷲尾隆, 永井健治, "遺伝子工学的に開発した蛍光プローブによる細胞生理機能超解像イメージング," 第31回人工知能学会全国大会, 2I4-OS-10b-4, 名古屋, 2017年5月.

2016年以前

2016年以前については、各メンバーのサイトをご参照ください。