E-LIB Suche - Ergebnisse für: Kudo, Mineichi

1

Sensor Data Simulation for Anomaly Detection of the Elderly..:

Tanaka, Kai ; Kudo, Mineichi ; Kimura, Keigo
IEEE Internet of Things Journal. , 2024

Link: https://doi.org/10.1109/..

2

Robust embedding regression for semi-supervised learning:

Bao, Jiaqi ; Kudo, Mineichi ; Kimura, Keigo.
Pattern Recognition. 145 (2024) - p. 109894 , 2024

Link: https://doi.org/10.1016/..

3

Redirected transfer learning for robust multi-layer subspac..:

Bao, Jiaqi ; Kudo, Mineichi ; Kimura, Keigo.
Pattern Analysis and Applications. 27 (2024) 1 - p. , 2024

Link: https://doi.org/10.1007/..

4

Incomplete Multi-view Weak-Label Learning with Noisy Featur..:

, In: PRICAI 2023: Trends in Artificial Intelligence; Lecture Notes in Computer Science,

Li, Zhiwei ; Yang, Zijian ; Sun, Lu.. - p. 124-130 , 2023

Link: https://doi.org/10.1007/..

5

Multi-Label Personalized Classification via Exclusive Spars..:

, In: 2023 IEEE International Conference on Data Mining (ICDM),

Lin, Weijia ; Wang, Jiankun ; Sun, Lu.. - p. 398-407 , 2023

Link: https://doi.org/10.1109/..

6

Partial Multi-label Learning with a Few Accurately Labeled ..:

, In: PRICAI 2023: Trends in Artificial Intelligence; Lecture Notes in Computer Science,

Mizuguchi, Haruhi ; Kimura, Keigo ; Kudo, Mineichi. - p. 79-90 , 2023

Link: https://doi.org/10.1007/..

7

Sensor Data Simulation with Wandering Behavior for the Elde..:

, In: 2022 26th International Conference on Pattern Recognition (ICPR),

Tanaka, Kai ; Kudo, Mineichi ; Kimura, Keigo - p. 885-891 , 2022

Link: https://doi.org/10.1109/..

8

Kernelized Supervised Laplacian Eigenmap for Visualization ..:

Tai, Mariko ; Kudo, Mineichi ; Tanaka, Akira..
Pattern Recognition. 123 (2022) - p. 108399 , 2022

Link: https://doi.org/10.1016/..

9

Retargeted Regression Methods for Multi-label Learning:

, In: Lecture Notes in Computer Science; Structural, Syntactic, and Statistical Pattern Recognition,

Kimura, Keigo ; Bao, Jiaqi ; Kudo, Mineichi. - p. 203-212 , 2022

Link: https://doi.org/10.1007/..

10

Efficient Leave-One-Out Evaluation of Kernelized Implicit M..:

, In: Lecture Notes in Computer Science; Structural, Syntactic, and Statistical Pattern Recognition,

Kudo, Mineichi ; Kimura, Keigo ; Morishita, Shumpei. - p. 223-232 , 2022

Link: https://doi.org/10.1007/..

11

Realization of Autoencoders by Kernel Methods:

, In: Lecture Notes in Computer Science; Structural, Syntactic, and Statistical Pattern Recognition,

Morishita, Shumpei ; Kudo, Mineichi ; Kimura, Keigo. - p. 1-10 , 2022

Link: https://doi.org/10.1007/..

12

Feature Selection with Class Hierarchy for Imbalance Proble..:

, In: Progress in Artificial Intelligence and Pattern Recognition; Lecture Notes in Computer Science,

Horio, Tomoya ; Kudo, Mineichi - p. 229-238 , 2021

Link: https://doi.org/10.1007/..

13

HVS : hierarchical graph structure based on voronoi diag..:

Lu, Kejing ; Kudo, Mineichi ; Xiao, Chuan.
Proceedings of the VLDB Endowment. 15 (2021) 2 - p. 246-258 , 2021

Link: https://dl.acm.org/doi/1..

14

MLSH: Mixed Hash Function Family for Approximate Nearest Ne..:

, In: Database Systems for Advanced Applications; Lecture Notes in Computer Science,

Lu, Kejing ; Kudo, Mineichi - p. 569-584 , 2021

Link: https://doi.org/10.1007/..

15

SVM Based EVM for Open Space Problems:

, In: Progress in Artificial Intelligence and Pattern Recognition; Lecture Notes in Computer Science,

Kaneko, Yasuyuki ; Kudo, Mineichi - p. 239-248 , 2021

Link: https://doi.org/10.1007/..