基本情報

所属

• 情報科学研究院　情報理工学部門　数理科学分野

職名

• 助教

J-Global ID

• 202101020525036094

研究キーワード

• 機械学習,データマイニング   

担当教育組織

•  学士課程　工学部
•  修士課程　情報科学院
•  博士課程　情報科学院

研究活動情報

論文

• Robust embedding regression for semi-supervised learning.

  Jiaqi Bao, Mineichi Kudo, Keigo Kimura, Lu Sun 0001

  Pattern Recognit. 145 109894 - 109894 2024年01月
• Incomplete Multi-view Weak-Label Learning with Noisy Features and Imbalanced Labels.

  Zhiwei Li 0007, Zijian Yang, Lu Sun, Mineichi Kudo, Keigo Kimura

  PRICAI (2) 124 - 130 2023年
• Partial Multi-label Learning with a Few Accurately Labeled Data.

  Haruhi Mizuguchi, Keigo Kimura, Mineichi Kudo, Lu Sun 0001

  PRICAI (2) 79 - 90 2023年
• Structured Sparse Multi-Task Learning with Generalized Group Lasso.

  Luhuan Fei, Lu Sun 0001, Mineichi Kudo, Keigo Kimura

  ECAI 692 - 699 2023年
• Efficient Leave-One-Out Evaluation of Kernelized Implicit Mappings.

  Mineichi Kudo, Keigo Kimura, Shumpei Morishita, Lu Sun 0001

  Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops(S+SSPR) 223 - 232 2022年
• Retargeted Regression Methods for Multi-label Learning.

  Keigo Kimura, Jiaqi Bao, Mineichi Kudo, Lu Sun 0001

  Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops(S+SSPR) 203 - 212 2022年
• Realization of Autoencoders by Kernel Methods.

  Shumpei Morishita, Mineichi Kudo, Keigo Kimura, Lu Sun 0001

  Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops(S+SSPR) 1 - 10 2022年
• Sensor Data Simulation with Wandering Behavior for the Elderly Living Alone.

  Kai Tanaka, Mineichi Kudo, Keigo Kimura

  26th International Conference on Pattern Recognition(ICPR) 885 - 891 2022年
• Kernelized Supervised Laplacian Eigenmap for Visualization and Classification of Multi-Label Data.

  Mariko Tai, Mineichi Kudo, Akira Tanaka, Hideyuki Imai, Keigo Kimura

  Pattern Recognition 123 108399 - 108399 2022年 [査読有り]
  
• MLC Toolbox: A MATLAB/OCTAVE Library for Multi-Label Classification.

  Keigo Kimura, Lu Sun 0001, Mineichi Kudo

  CoRR abs/1704.02592 2017年 [査読無し]
  
• READER: Robust Semi-Supervised Multi-Label Dimension Reduction.

  Lu Sun 0001, Mineichi Kudo, Keigo Kimura

  IEICE Transactions on Information & Systems 100-D 10 2597 - 2604 2017年 [査読有り]
  
• Simultaneous Nonlinear Label-Instance Embedding for Multi-label Classification.

  Keigo Kimura, Mineichi Kudo, Lu Sun 0001

  Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop(S+SSPR) 15 - 25 2016年 [査読有り]
  
• Simultaneous visualization of samples, features and multi-labels.

  Mineichi Kudo, Keigo Kimura, Michal Haindl, Hiroshi Tenmoto

  23rd International Conference on Pattern Recognition(ICPR) 3603 - 3608 2016年 [査読有り]
  
• Locality in multi-label classification problems.

  Batzaya Norov-Erdene, Mineichi Kudo, Lu Sun 0001, Keigo Kimura

  23rd International Conference on Pattern Recognition(ICPR) 2319 - 2324 2016年 [査読有り]
  
• Multi-label classification with meta-label-specific features.

  Lu Sun 0001, Mineichi Kudo, Keigo Kimura

  23rd International Conference on Pattern Recognition(ICPR) 1612 - 1617 2016年 [査読有り]
  
• Fast random k-labELsets for large-scale multi-label classification.

  Keigo Kimura, Mineichi Kudo, Lu Sun 0001, Sadamori Koujaku

  23rd International Conference on Pattern Recognition(ICPR) 438 - 443 2016年 [査読有り]
  
• A Scalable Clustering-Based Local Multi-Label Classification Method.

  Lu Sun 0001, Mineichi Kudo, Keigo Kimura

  ECAI 2016 - 22nd European Conference on Artificial Intelligence(ECAI) 261 - 268 2016年 [査読有り]
  
• A column-wise update algorithm for nonnegative matrix factorization in Bregman divergence with an orthogonal constraint.

  Keigo Kimura, Mineichi Kudo, Yuzuru Tanaka

  Machine Learning 103 2 285 - 306 2016年 [査読有り]
  
• Dimension Reduction Using Nonnegative Matrix Tri-Factorization in Multi-label Classification.

  Keigo Kimura, Mineichi Kudo, Lu Sun

  Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA) 250  2015年07月 [査読有り]
  
• Variable Selection for Efficient Nonnegative Tensor Factorization.

  Keigo Kimura, Mineichi Kudo

  2015 IEEE International Conference on Data Mining(ICDM) 805 - 810 2015年 [査読有り]
  
• A Fast Hierarchical Alternating Least Squares Algorithm for Orthogonal Nonnegative Matrix Factorization.

  Keigo Kimura, Yuzuru Tanaka, Mineichi Kudo

  Proceedings of the Sixth Asian Conference on Machine Learning(ACML) 2014年 [査読有り]
  
• Topic graph based transfer learning via generalized KL divergence based NMF.

  Keigo Kimura, Tetsuya Yoshida

  2011 IEEE International Conference on Granular Computing(GrC) 330 - 335 2011年 [査読有り]
  
• Non-negative Matrix Factorization with sparse features.

  Keigo Kimura, Tetsuya Yoshida

  2011 IEEE International Conference on Granular Computing(GrC) 324 - 329 2011年 [査読有り]