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2020 – today
- 2024
[j6]Kai Tanaka
, Mineichi Kudo, Keigo Kimura:
Sensor Data Simulation for Anomaly Detection of the Elderly Living Alone. IEEE Internet Things J. 11(19): 31675-31686 (2024)- [j5]Jiaqi Bao, Mineichi Kudo, Keigo Kimura, Lu Sun:
Redirected transfer learning for robust multi-layer subspace learning. Pattern Anal. Appl. 27(1): 25 (2024) - [j4]Jiaqi Bao, Mineichi Kudo, Keigo Kimura, Lu Sun:
Robust embedding regression for semi-supervised learning. Pattern Recognit. 145: 109894 (2024) - [c25]Kai Tanaka, Mineichi Kudo, Keigo Kimura:
Fall Detection by Ambient Sensors on Years-Long Simulation Data. ABC 2024: 1-8 - 2023
- [c24]Luhuan Fei, Lu Sun, Mineichi Kudo, Keigo Kimura:
Structured Sparse Multi-Task Learning with Generalized Group Lasso. ECAI 2023: 692-699 - [c23]Keigo Kimura, Mitsuyoshi Imamura, Kazumasa Omote:
Cross-Referencing Scheme to Ensure NFT and Platform Linkage Unaffected by Forking. ICBC 2023: 1-4 - [c22]Weijia Lin, Jiankun Wang, Lu Sun, Mineichi Kudo, Keigo Kimura:
Multi-Label Personalized Classification via Exclusive Sparse Tensor Factorization. ICDM 2023: 398-407 - [c21]Haruhi Mizuguchi, Keigo Kimura, Mineichi Kudo, Lu Sun:
Partial Multi-label Learning with a Few Accurately Labeled Data. PRICAI (2) 2023: 79-90 - [c20]Zhiwei Li, Zijian Yang, Lu Sun, Mineichi Kudo, Keigo Kimura:
Incomplete Multi-view Weak-Label Learning with Noisy Features and Imbalanced Labels. PRICAI (2) 2023: 124-130 - [i2]Kai Tanaka, Mineichi Kudo, Keigo Kimura:
Sensor Data Simulation for Anomaly Detection of the Elderly Living Alone. CoRR abs/2312.16852 (2023) - 2022
- [j3]Mariko Tai, Mineichi Kudo, Akira Tanaka, Hideyuki Imai, Keigo Kimura:
Kernelized Supervised Laplacian Eigenmap for Visualization and Classification of Multi-Label Data. Pattern Recognit. 123: 108399 (2022) - [c19]Keigo Kimura, Mitsuyoshi Imamura, Kazumasa Omote:
A Distributed Authenticity Verification Scheme Using Deep Learning for NFT Market. ICBTA 2022: 40-49 - [c18]Kai Tanaka, Mineichi Kudo, Keigo Kimura:
Sensor Data Simulation with Wandering Behavior for the Elderly Living Alone. ICPR 2022: 885-891 - [c17]Shumpei Morishita, Mineichi Kudo, Keigo Kimura, Lu Sun:
Realization of Autoencoders by Kernel Methods. S+SSPR 2022: 1-10 - [c16]Keigo Kimura, Jiaqi Bao, Mineichi Kudo, Lu Sun:
Retargeted Regression Methods for Multi-label Learning. S+SSPR 2022: 203-212 - [c15]Mineichi Kudo, Keigo Kimura, Shumpei Morishita, Lu Sun:
Efficient Leave-One-Out Evaluation of Kernelized Implicit Mappings. S+SSPR 2022: 223-232 - 2021
- [c14]Keigo Kimura, Kazumasa Omote:
Risk Analysis for Abusing Blockchain Poisoning. BRAINS 2021: 45-46
2010 – 2019
- 2019
- [c13]Keigo Kimura, Kandai Mochizuki, Masafumi Koike, Osamu Mizuno:
Data Transfer Methods for Information-Centric Networking-Based Wireless Sensor Network Platform. ICOIN 2019: 336-341 - 2017
- [j2]Lu Sun, Mineichi Kudo, Keigo Kimura:
READER: Robust Semi-Supervised Multi-Label Dimension Reduction. IEICE Trans. Inf. Syst. 100-D(10): 2597-2604 (2017) - [i1]Keigo Kimura, Lu Sun, Mineichi Kudo:
MLC Toolbox: A MATLAB/OCTAVE Library for Multi-Label Classification. CoRR abs/1704.02592 (2017) - 2016
- [j1]Keigo Kimura, Mineichi Kudo, Yuzuru Tanaka:
A column-wise update algorithm for nonnegative matrix factorization in Bregman divergence with an orthogonal constraint. Mach. Learn. 103(2): 285-306 (2016) - [c12]Lu Sun, Mineichi Kudo, Keigo Kimura:
A Scalable Clustering-Based Local Multi-Label Classification Method. ECAI 2016: 261-268 - [c11]Keigo Kimura, Mineichi Kudo, Lu Sun, Sadamori Koujaku:
Fast random k-labELsets for large-scale multi-label classification. ICPR 2016: 438-443 - [c10]Lu Sun, Mineichi Kudo, Keigo Kimura:
Multi-label classification with meta-label-specific features. ICPR 2016: 1612-1617 - [c9]Batzaya Norov-Erdene, Mineichi Kudo, Lu Sun, Keigo Kimura:
Locality in multi-label classification problems. ICPR 2016: 2319-2324 - [c8]Mineichi Kudo, Keigo Kimura, Michal Haindl, Hiroshi Tenmoto:
Simultaneous visualization of samples, features and multi-labels. ICPR 2016: 3603-3608 - [c7]Keigo Kimura, Mineichi Kudo, Lu Sun:
Simultaneous Nonlinear Label-Instance Embedding for Multi-label Classification. S+SSPR 2016: 15-25 - 2015
- [c6]Keigo Kimura, Mineichi Kudo:
Variable Selection for Efficient Nonnegative Tensor Factorization. ICDM 2015: 805-810 - 2014
- [c5]Keigo Kimura, Yuzuru Tanaka, Mineichi Kudo:
A Fast Hierarchical Alternating Least Squares Algorithm for Orthogonal Nonnegative Matrix Factorization. ACML 2014 - 2011
- [c4]Keigo Kimura, Tetsuya Yoshida:
Non-negative Matrix Factorization with sparse features. GrC 2011: 324-329 - [c3]Keigo Kimura, Tetsuya Yoshida:
Topic graph based transfer learning via generalized KL divergence based NMF. GrC 2011: 330-335
2000 – 2009
- 2008
- [c2]Ibuki Mori, Keigo Kimura, Yoshihisa Yamada, Haruo Kobayashi, Yasunori Kobori, Santhos Ario Wibowo, Kazuya Shimizu, Masashi Kono, Hao San:
High-resolution DPWM generator for digitally controlled DC-DC converters. APCCAS 2008: 914-917 - 2006
- [c1]O. Ishibashi, M. Iriguchi, Keigo Kimura, J. Ishii, D. Sasaki, Hideyuki Imai, H. Tsuchi, Hiroshi Hayama:
Panel-Sized TFT-LCD Column Driver. ISSCC 2006: 619-626
Coauthor Index
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last updated on 2024-10-15 20:46 CEST by the dblp team
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