Faculty Detail / 研究室詳細



Computational neuroscience, Dynamic tensor analysis, Brain/human computer interactions

Andrzej, Cichocki


当研究室では、多次元かつ大容量な生体データがもつ複雑なメカニズムを解明するための、人工知能(AI)や機械学習(ML)、計算論的神経科学などの数理的アプローチについて研究しています。 そのため、多重線形な独立成分分析(ICA)、非負行列分解(NMF)、スパース成分分析(SCA)、テンソル分解のための新しいアルゴリズム・ソフトウェア開発、特にテンソルネットワーク、ディープニューラルネットワークなどの革新的技術を用いて、多次元で大容量なデータを処理する技術(特徴抽出、パターン認識、クラスタリング、異常検出など)の開発に力を注いでいます。

主な発表論文 全て表示する

  1. 1

    Yokota T, Lee N, and Cichocki A: "Robust multilinear tensor rank estimation using higher order singular value decomposition and information criteria", IEEE Transactions on Signal Processing, 65(5), 1196-1206 (2017)

  2. 2

    Thiyam D.B., Cruces S, Olias J, and Cichocki A.: "Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements", Entropy , 19(3), 89 (2017)

  3. 3

    Cichocki A, Lee N, Oseledets I.V., Phan A-H., Zhao Q, and Mandic D. : "Tensor Networks for Dimensionality Reduction and Large-Scale Optimization: Part 1 Low-Rank Tensor Decompositions", Foundation and Trends in Machine Learning, 9(4-5), 249-429 (2016)

  4. 4

    Yokota T, Zhao Q, and Cichocki A.: "Smooth PARAFAC decomposition for tensor completion", IEEE Trans. Signal Processing , 64(20), 5423-5436 (2016)

  5. 5

    Zhou S, Allison B.Z., Kübler A, Cichocki A, Wang X, and Jin J. : "Effects of background music on objective and subjective performance measures in an auditory BCI", Frontiers in Computational Neuroscience , 10(105) (2016)

  6. 6

    Lee N, and Cichocki A.: "Regularized computation of approximate pseudoinverse of large matrices using low-rank tensor train decompositions", SIAM J. Matrix Analysis Applications, 37(2), 598-623 (2016)

  7. 7

    Zhao Q, Zhou G, Zhang L, Cichocki A, and Amari S. : "Bayesian robust tensor factorization for incomplete multiway data.", IEEE Transactions on Neural Networks and Learning Systems, 27(4), 736-748 (2016)

  8. 8

    Zhou G, Zhao Q, Zhang Y, Adali T, Xie S, and Cichocki A. : "Linked component analysis from matrices to high order tensors: Applications to biomedical data", Proceedings of the IEEE, 104(2), 310-331 (2016)

  9. 9

    Cichocki A, Mandic D, Caiafa C, Phan A-H, Zhou G, Zhao Q, and De Lathauwer L.: "Tensor Decompositions for Signal Processing Applications. From Two-way to Multiway Component Analysis", IEEE Signal Processing Magazine, 32(2), 145-163 (2015)

  10. 10

    Cichocki A, Cruces S, and Amari S.: "Log-Determinant Divergences Revisited: Alpha-Beta and Gamma Log-Det Divergences", Entropy, 17(5), 2988-3034 (2015)

  11. 11

    Zhou G, Cichocki A, Zhang Y, and Mandic D. : "Group component analysis for multiblock data: common and individual feature extraction", IEEE Transactions on Neural Networks and Learning Systems, 27(11), 2426-2439 (2015)

  12. 12

    Caiafa C, and Cichocki A.: "Stable, Robust, and Super Fast Reconstruction of Tensor Using Multi-Way Projections", IEEE Trans. Signal Processing, 63(3), 780-793 (2015)

  13. 13

    Ma J, Zhang Y, Cichocki A, and Matsuno F: "A Novel EOG/EEG Hybrid Human-Machine Interface Adopting Eye Movements and ERPs: Application to Robot Control.", IEEE Trans. Biomedical Engineering, 62(3), 876-889 (2015)

  14. 14

    Zhao Q, Caiafa CF, Mandic D, Chao ZC, Nagasaka Y, Fujii N, Zhang L, and Cichocki A: "Higher-Order Partial Least Squares (HOPLS): A Generalized Multi-Linear Regression Method.", IEEE Trans Pattern Anal Mach Intell (2012)

  15. 15

    Vialatte FB, Maurice M, Dauwels J, and Cichocki A: "Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.", Prog Neurobiol, 90(4), 418-38 (2010)

  16. 16

    Cichocki A, and Phan AH: "Fast Local Algorithms for Large Scale Nonnegative Matrix and Tensor Factorizations.", IEICE Trans. Fundamentals, E92-A(3), 708-721. (2009)

  17. 17

    Dauwels JHG, Vialatte FB, and Cichocki A: "A Comparative Study of Synchrony Measures for the Early Detection of Alzheimer's Disease Based on EEG", Lecture Notes in Computer Science, 4984, 112--125 (2008)

  18. 18

    Cichocki A, Shishkin SL, Musha T, Leonowicz Z, Asada T, and Kurachi T: "EEG filtering based on blind source separation (BSS) for early detection of Alzheimer's disease.", Clin Neurophysiol, 116(3), 729-37 (2005)

  19. 19

    Cichocki A, and Amari S: "Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. (550 pages)", monograph Wiley (2003)