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Koichiro Yamauchi 0001
Person information
- affiliation: Chubu University, Computer Science, Japan
- affiliation: Hokkaido University, Japan
- affiliation: Nagoya Institute of Technology, Japan
Other persons with the same name
- Koichiro Yamauchi 0002 — Aishin AW Co., Ltd. (and 3 more)
- Koichiro Yamauchi 0003 — Woven by Toyota, Inc., Tokyo, Japan
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2020 – today
- 2024
- [c45]Taihei Asai, Koichiro Yamauchi:
Swap-Deep Neural Network: Incremental Inference and Learning for Embedded Systems. ICPRAM 2024: 418-427 - [c44]Tatsuya Hori, Koichiro Yamauchi
:
Low Cost Active Learning Framework for Short Answer Scoring. PKAW 2024: 176-189 - [c43]Nozomi Kitagawa, Koichiro Yamauchi
Virtual Learning Machine for Tiny Devices. PKAW 2024: 276-288 - 2023
- [j13]Koichiro Yamauchi
Quick continual kernel learning on bounded memory space based on balancing between adaptation and forgetting. Evol. Syst. 14(3): 437-460 (2023) - 2021
- [c42]Abhilash Reddy Shankarampeta
Few-Shot Class Incremental Learning with Generative Feature Replay. ICPRAM 2021: 259-267
2010 – 2019
- 2019
- [c41]Masaharu Yamamoto
Swap Kernel Regression. ICANN (1) 2019: 223-238 - [c40]Taiki Watanabe, Koichiro Yamauchi
Lightweight Modal Regression for Stand Alone Embedded Systems. ICONIP (2) 2019: 367-379 - [c39]Ashwin Devanga, Koichiro Yamauchi
Collaborative Learning of Human and Computer: Supervised Actor-Critic based Collaboration Scheme. ICPRAM 2019: 794-801 - 2018
- [c38]Koichiro Yamauchi
Minimum Modal Regression. ICPRAM 2018: 448-455 - 2016
- [j12]Takaya Ogiso, Koichiro Yamauchi
Co-learning system for humans and machines using a weighted majority-based method. Int. J. Hybrid Intell. Syst. 13(1): 63-76 (2016) - [c37]Kazuyoshi Kato, Koichiro Yamauchi:
Risk Sensitive Reinforcement Learning Scheme Is Suitable for Learning on a Budget. ICONIP (3) 2016: 202-210 - [c36]Daisuke Nishio, Koichiro Yamauchi:
Multithreading Incremental Learning Scheme for Embedded System to Realize a High-Throughput. ICONIP (2) 2016: 204-213 - 2015
- [c35]Akihisa Kato, Hirohito Kawahara, Koichiro Yamauchi
Incremental learning on a budget and a quick calculation method using a tree-search algorithm. IJCNN 2015: 1-7 - [c34]Takaya Ogiso, Koichiro Yamauchi, Norio Ishii, Yuri Suzuki:
A co-learning system for humans and machines. SoCPaR 2015: 363-368 - 2014
- [j11]Koichiro Yamauchi
Incremental Learning on a Budget and its Application to Quick Maximum Power Point Tracking of Photovoltaic Systems. J. Adv. Comput. Intell. Intell. Informatics 18(4): 682-696 (2014) - [c33]Yusuke Kondo, Koichiro Yamauchi:
A Dynamic Pruning Strategy for Incremental Learning on a Budget. ICONIP (1) 2014: 295-303 - [c32]Kenta Igushi, Takaya Ogiso, Koichiro Yamauchi
Acceleration of reinforcement learning via game-based renewal energy management system. SCIS&ISIS 2014: 415-420 - 2013
- [c31]Koichiro Yamauchi
Incremental Learning on a Budget and Its Application to Power Electronics. ICONIP (2) 2013: 341-351 - [c30]Koichiro Yamauchi
An importance weighted projection method for incremental learning under unstationary environments. IJCNN 2013: 1-9 - 2012
- [c29]Koichiro Yamauchi:
Incremental learning on a budget and its application to quick maximum power point tracking of photovoltaic systems. SCIS&ISIS 2012: 71-78 - 2011
- [j10]Koichiro Yamauchi
Incremental model selection and ensemble prediction under virtual concept drifting environments. Evol. Syst. 2(4): 249-260 (2011) - [c28]Koichiro Yamauchi
Pruning with replacement and automatic distance metric detection in limited general regression neural networks. IJCNN 2011: 899-906 - 2010
- [j9]Kazutaka Kouda, Takashi Omori, Koichiro Yamauchi, Satoru Ishikawa:
Modeling of Car Driver Cognitive Process Based on Hazard Perception in Front of Car. Aust. J. Intell. Inf. Process. Syst. 11(3) (2010) - [j8]Yasushi Kohata, Koichiro Yamauchi
High-Speed Maximum Power Point Tracker for Photovoltaic Systems Using Online Learning Neural Networks. J. Adv. Comput. Intell. Intell. Informatics 14(6): 677-682 (2010) - [c27]Koichiro Yamauchi
Incremental learning and model selection under virtual concept drifting environments. IJCNN 2010: 1-8 - [c26]Koichiro Yamauchi:
Incremental Model Selection and Ensemble Prediction under Virtual Concept Drifting Environments. PRICAI 2010: 570-582
2000 – 2009
- 2009
- [j7]Koichiro Yamauchi
Optimal incremental learning under covariate shift. Memetic Comput. 1(4): 271-279 (2009) - [c25]Yasushi Kohata, Koichiro Yamauchi
Quick Maximum Power Point Tracking of Photovoltaic Using Online Learning Neural Network. ICONIP (1) 2009: 606-613 - [c24]Kyosuke Nishida, Koichiro Yamauchi
Learning, detecting, understanding, and predicting concept changes. IJCNN 2009: 2280-2287 - [c23]Takashi Omori, Masayoshi Sato, Koichiro Yamauchi, Satoru Ishikawa, Toshihiro Wakita
Computational Modeling of Risk-Dependent Eye Movements of Car Drivers. SMC 2009: 2457-2461 - 2008
- [c22]Masayoshi Sato, Yuki Togashi, Takashi Omori, Koichiro Yamauchi, Satoru Ishikawa, Toshihiro Wakita
Computational Modeling of Risk-Related Eye Movement of Car Drivers. ICONIP (1) 2008: 293-300 - [c21]Koichiro Yamauchi
Covariate Shift and Incremental Learning. ICONIP (1) 2008: 1154-1162 - [c20]Kyosuke Nishida, Shohei Shimada, Satoru Ishikawa, Koichiro Yamauchi:
Detecting sudden concept drift with knowledge of human behavior. SMC 2008: 3261-3267 - 2007
- [j6]Koichiro Yamauchi
Incremental Leaning and Model Selection for Radial Basis Function Network through Sleep. IEICE Trans. Inf. Syst. 90-D(4): 722-735 (2007) - [c19]Kyosuke Nishida, Koichiro Yamauchi
Detecting Concept Drift Using Statistical Testing. Discovery Science 2007: 264-269 - [c18]Yuki Togashi, Takashi Omori, Koichiro Yamauchi:
Model of driver eye motion based on driving plan and prediction of changes in the environment. FOCI 2007: 289-295 - [c17]Koichiro Yamauchi, Masayoshi Sato:
Incremental Learning of Spatio-temporal Patterns with Model Selection. ICANN (1) 2007: 149-158 - [c16]Jiro Hayami, Koichiro Yamauchi
PLS Mixture Model for Online Dimension Reduction. ICONIP (1) 2007: 279-288 - [c15]Youhei Tadeuchi, Ryuji Oshima, Kyosuke Nishida, Koichiro Yamauchi, Takashi Omori:
Quick online feature selection method for regression -A feature selection method inspired by human behavior-. SMC 2007: 1895-1900 - 2006
- [j5]Kyosuke Nishida, Koichiro Yamauchi, Takashi Omori:
An online learning algorithm with dimension selection using minimal hyper basis function networks. Syst. Comput. Jpn. 37(11): 11-21 (2006) - [c14]Koichiro Yamauchi, Jiro Hayami:
Sleep Learning - An Incremental Learning System Inspired by Sleep Behavior-. FUZZ-IEEE 2006: 1186-1193 - 2005
- [j4]Koichiro Yamauchi, Takayuki Oohira, Takashi Omori:
Fast incremental learning methods inspired by biological learning behavior. Artif. Life Robotics 9(3): 128-134 (2005) - [c13]Kyosuke Nishida, Koichiro Yamauchi, Takashi Omori:
ACE: Adaptive Classifiers-Ensemble System for Concept-Drifting Environments. Multiple Classifier Systems 2005: 176-185 - 2004
- [c12]Koichiro Yamauchi:
Incremental Learning and Dimension Selection Through Sleep. ICONIP 2004: 489-495 - [c11]Kyosuke Nishida, Koichiro Yamauchi, Takashi Omori:
An On-Line Learning Algorithm with Dimension Selection Using Minimal Hyper Basis Function Networks. ICONIP 2004: 502-507 - 2003
- [j3]Hiromi Takeuchi, Yoshifumi Terabayashi, Koichiro Yamauchi, Naohiro Ishii:
Improvement of Robot Sensor by Integrating Information Using Neural Network. Int. J. Artif. Intell. Tools 12(2): 139-152 (2003) - [c10]Takayuki Oohira, Koichiro Yamauchi, Takashi Omori:
Meta-learning for Fast Incremental Learning. ICANN 2003: 157-164 - 2001
- [c9]Mikiya Oota, Naohiro Ishii, Koichiro Yamauchi, Mayumi Nakamura:
Optimization with Linear Constraints in the Neural Network. IWANN (1) 2001: 561-569 - 2000
- [c8]Kazunori Iwata
Combining Exploitation-Based and Exploration-Based Approach in Reinforcement Learning. IDEAL 2000: 326-331
1990 – 1999
- 1999
- [j2]Koichiro Yamauchi, Mikiya Oota, Naohiro Ishii:
A self-supervised learning system for pattern recognition by sensory integration. Neural Networks 12(10): 1347-1358 (1999) - [j1]Koichiro Yamauchi, Nobuhiko Yamaguchi, Naohiro Ishii:
Incremental learning methods with retrieving of interfered patterns. IEEE Trans. Neural Networks 10(6): 1351-1365 (1999) - 1998
- [c7]Sachio Itoh, Shinji Ishiguro, Koichiro Yamauchi, Naohiro Ishii:
Face Image Segmentation by Detecting Attentive Regions of Artificial Neural Network. ICONIP 1998: 364-368 - [c6]Koichiro Yamauchi, Naohiro Ishii:
Combination of Fast and Slow Learning Methods for Fast Adaptation and Pruning of Redundant Cells. ICONIP 1998: 757-760 - [c5]Koichiro Yamauchi, Toshie Imai, Naohiro Ishii:
An Incremental Learning Method of GRBF with Re-Generation of Input Patterns - Application for Case Based Reasoning Systems. ICONIP 1998: 761-766 - 1997
- [c4]Koichiro Yamauchi, Satoshi Sugiura, Naohiro Ishii:
Self-Supervised Learning of Autonomous Robot by Integrating Information from Several Sensors. ICONIP (1) 1997: 149-152 - [c3]Koichiro Yamauchi, Nobuhiko Yamaguchi, Naohiro Ishii:
Incremental Learning Method of GRBF with Recalling of Interfered Patterns - Application for Case Based Reasoning Systems. ICONIP (2) 1997: 859-864 - 1996
- [c2]Koichiro Yamauchi, Mikiya Oota, Naohiro Ishii:
A Self-Supervised Learning System for Category Detection by Integrating Information from Several Sensors. International Conference on Evolutionary Computation 1996: 694-699 - 1995
- [c1]Koichiro Yamauchi, Naohiro Ishii:
An incremental learning method with recalling interfered patterns. ICNN 1995: 3159-3164
Coauthor Index
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