This is the top of the page.
Displaying present location in the site.
  1. Home
  2. About NEC
  3. Research & Development
  4. NEC R&D Members
  5. Keigo Kimura
Main content starts here.

NEC R&D Members

Keigo Kimura

Security Laboratory,
NEC Central Research Labs.
Ph.D. (Information Science)

Research Area

  • Data Mining, Machine Learning

Journal

  • Keigo Kimura, Mineichi Kudo and Yuzuru Tanaka, "A Column-wise Update Algorithm for Nonnegative Matrix Factorization in Bregman Divergence with Orthogonal Constraint", Machine Learning, 103-2(2016), 285-306.
  • Lu Sun, Mineichi Kudo and Keigo Kimura, "READER: Robust Semi-Supervised Multi-Label Dimension Reduction," IEICE Transactions on Information and Systems, 2017.

International Conference

  • Lu Sun, Mineichi Kudo and Keigo Kimura, "Multi-Label Classification with Meta-Label-Specific Features." in Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico.
  • Keigo Kimura, Mineichi Kudo, Lu Sun and Sadamori Koujaku, "Fast Random k-labelsets for Large-Scale Multi-Label Classification." in Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico.
  • Batzaya Norov-Erdene, Mineichi Kudo, Lu Sun and Keigo Kimura, "Locality in Multi-Label Classification Problems." in Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico.
  • Mineichi Kudo, Keigo Kimura, Michael Haindl, Hiroshi Tenmoto, " Simultaneous Visualization of Samples, Features and Multi-Labels." in Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico.
  • Keigo Kimura, Mineichi Kudo, Lu Sun, "Simultaneous Nonlinear Label-Instance Embedding for Multi-label Classification." in Proceedings of the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition and Statistical Techniques in Pattern Recognition (S+SSPR 2016), Merida, Mexico.
  • Keigo Kimura and Mineichi Kudo, "Dimension Reduction Using Nonnegative Matrix Tri-Factorization in Multi-label Classification." Proceedings of The 2015 International Conference on Parallel & Distributed Processing Techniques & Applications: Workshop on Mathematical Modeling and Problem Solving, 2015, 250-255.
  • Keigo Kimura and Mineichi Kudo, "Variable Selection for Efficient Nonnegative Tensor Factorization." In Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM), Nov. 2015, 805 – 810.
  • Lu Sun, Mineichi Kudo and Keigo Kimura, "A Scalable Clustering-Based Local Multi-Label Classification Method." in Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016), 261-268, 2016, The Hague, Netherlands.
  • Keigo Kimura, Yuzuru Tanaka and Mineichi Kudo, "A Fast hierarchical Alternating Least Squares Algorithm for Orthogonal Nonnegative Matrix Factorization." In proceedings of the 6th Asian Conference on Machine Learning (ACML), 2014, p.129-141.

Biography

  • 2008-2012Hokkaido University (Bachelor)
  • 2012-2014Graduate School of Information Science and Technology, Hokkaido University. (Master)
  • 2014-2017Graduate School of Information Science and Technology, Hokkaido University. (Ph.D.)
  • 2014-2017JSPS Research Fellowship for Young Scientists. (DC1)
  • 2017-NEC Security Laboratories.

Awards

  • IPSJ-MPS85 Presentation Award, September 2011.
  • JSPS Research Fellowship for Young Scientists (DC1)
  • Student Travel Grant @IEEE International Conference on Data Mining, November 2015.
  • IAPR Travel Stipend for ICPR 2016, December 2016
  • Dean's Award for my doctoral thesis "A Study on Efficient Algorithms for Nonnegative Matrix/Tensor Factorization",

Pre-Print and Software

  • Keigo Kimura, Lu Sun, Mineichi Kudo:
    MLC Toolbox: A MATLAB/OCTAVE Library for Multi-Label Classification.CoRR abs/1704.02592 (2017)

Top of this page