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Tomoumi Takase
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Cited by
Year
Effective neural network training with adaptive learning rate based on training loss
T Takase, S Oyama, M Kurihara
Neural Networks 101, 68-78, 2018
1232018
Dynamic batch size tuning based on stopping criterion for neural network training
T Takase
Neurocomputing 429, 1-11, 2021
212021
Self-paced data augmentation for training neural networks
T Takase, R Karakida, H Asoh
Neurocomputing 442, 296-306, 2021
162021
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
132018
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
72023
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
52018
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
32021
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
32019
Feature combination mixup: novel mixup method using feature combination for neural networks
T Takase
Neural Computing and Applications 35 (17), 12763-12774, 2023
22023
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
12019
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
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