Tomoumi Takase

According to our database, Tomoumi Takase authored at least 12 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Feature combination mixup: novel mixup method using feature combination for neural networks.

Tomoumi Takase

Neural Comput. Appl., June, 2023

Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias.

Ryo Karakida, Tomoumi Takase, Tomohiro Hayase, Kazuki Osawa

Proceedings of the International Conference on Machine Learning, 2023

2022

A Collaborative Training Using Crowdsourcing and Neural Networks on Small and Difficult Image Classification Datasets.

Tomoumi Takase

SN Comput. Sci., 2022

2021

Self-paced data augmentation for training neural networks.

Tomoumi Takase, Ryo Karakida, Hideki Asoh

Neurocomputing, 2021

Dynamic batch size tuning based on stopping criterion for neural network training.

Tomoumi Takase

Neurocomputing, 2021

Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer Mapping.

Suguru Kanoga, Tomoumi Takase, Takayuki Hoshino, Hideki Asoh

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2019

Difficulty-weighted learning: A novel curriculum-like approach based on difficult examples for neural network training.

Tomoumi Takase

Expert Syst. Appl., 2019

Evaluation of Stratified Validation in Neural Network Training with Imbalanced Data.

Tomoumi Takase, Satoshi Oyama, Masahito Kurihara

Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2019

2018

Effective neural network training with adaptive learning rate based on training loss.

Tomoumi Takase, Satoshi Oyama, Masahito Kurihara

Neural Networks, 2018

Why Does Large Batch Training Result in Poor Generalization? A Comprehensive Explanation and a Better Strategy from the Viewpoint of Stochastic Optimization.

Tomoumi Takase, Satoshi Oyama, Masahito Kurihara

Neural Comput., 2018

Longer Distance Weight Prediction for Faster Training of Neural Networks.

Masahito Kurihara, Satoshi Oyama, Tomoumi Takase

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges.

Yukino Baba, Tomoumi Takase, Kyohei Atarashi, Satoshi Oyama, Hisashi Kashima

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018