Effective neural network training with adaptive learning rate based on training loss T Takase, S Oyama, M Kurihara Neural Networks 101, 68-78, 2018 | 107 | 2018 |

Dynamic batch size tuning based on stopping criterion for neural network training T Takase Neurocomputing 429, 1-11, 2021 | 19 | 2021 |

Self-paced data augmentation for training neural networks T Takase, R Karakida, H Asoh Neurocomputing 442, 296-306, 2021 | 13 | 2021 |

Why does large batch training result in poor generalization? A comprehensive explanation and a better strategy from the viewpoint of stochastic optimization T Takase, S Oyama, M Kurihara Neural computation 30 (7), 2005-2023, 2018 | 12 | 2018 |

Understanding gradient regularization in deep learning: Efficient finite-difference computation and implicit bias R Karakida, T Takase, T Hayase, K Osawa International Conference on Machine Learning, 15809-15827, 2023 | 5 | 2023 |

Data analysis competition platform for educational purposes: lessons learned and future challenges Y Baba, T Takase, K Atarashi, S Oyama, H Kashima Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 5 | 2018 |

Evaluation of stratified validation in neural network training with imbalanced data T Takase, S Oyama, M Kurihara 2019 IEEE International Conference on Big Data and Smart Computing (BigComp …, 2019 | 3 | 2019 |

Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer Mapping S Kanoga, T Takase, T Hoshino, H Asoh 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 2 | 2021 |

Feature combination mixup: novel mixup method using feature combination for neural networks T Takase Neural Computing and Applications 35 (17), 12763-12774, 2023 | 1 | 2023 |

Difficulty-weighted learning: A novel curriculum-like approach based on difficult examples for neural network training T Takase Expert Systems with Applications 135, 83-89, 2019 | 1 | 2019 |

A Collaborative Training Using Crowdsourcing and Neural Networks on Small and Difficult Image Classification Datasets T Takase SN Computer Science 3 (2), 178, 2022 | | 2022 |

Longer Distance Weight Prediction for Faster Training of Neural Networks T Takase, S Oyama, M Kurihara 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | | 2018 |

ニューラルネットワークの効果的な訓練のための探索と収束の制御 高瀬朝海 北海道大学, 2018 | | 2018 |

形彫り放電加工の工具消耗における熱影響の調査 高瀬朝海， 国枝正典 精密工学会学術講演会講演論文集 2014 年度精密工学会春季大会, 1175-1176, 2014 | | 2014 |

形彫り放電加工の逆方向シミュレーションの揺動加工への適用 高瀬朝海， 国枝正典 電気加工学会全国大会講演論文集 2012, 37-40, 2012 | | 2012 |

D06 逆方向シミュレーションを用いた揺動放電加工の軌跡の導出 (OS8 電気加工 (2)) 高瀬朝海， 国枝正典 生産加工・工作機械部門講演会: 生産と加工に関する学術講演会 2012.9, 199-202, 2012 | | 2012 |

揺動放電加工の逆方向シミュレーションの試み 高瀬朝海， 国枝正典 精密工学会学術講演会講演論文集 2012 (0), 127-128, 2012 | | 2012 |