Kentaro Imajo

According to our database, Kentaro Imajo authored at least 13 papers between 2011 and 2024.

Collaborative distances:

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

2024

PLaMo-100B: A Ground-Up Language Model Designed for Japanese Proficiency.

Kenshin Abe, Kaizaburo Chubachi, Yasuhiro Fujita, Yuta Hirokawa, Kentaro Imajo, Toshiki Kataoka, Hiroyoshi Komatsu, Hiroaki Mikami, Tsuguo Mogami, Shogo Murai, Kosuke Nakago, Daisuke Nishino, Toru Ogawa, Daisuke Okanohara, Yoshihiko Ozaki, Shotaro Sano, Shuji Suzuki, Tianqi Xu, Toshihiko Yanase

CoRR, 2024

The Construction of Instruction-tuned LLMs for Finance without Instruction Data Using Continual Pretraining and Model Merging.

Masanori Hirano, Kentaro Imajo

CoRR, 2024

Construction of Domain-Specified Japanese Large Language Model for Finance Through Continual Pre-Training.

Masanori Hirano, Kentaro Imajo

Proceedings of the 16th IIAI International Congress on Advanced Applied Informatics, 2024

2023

Efficient Learning of Nested Deep Hedging using Multiple Options.

Masanori Hirano, Kentaro Imajo, Kentaro Minami, Takuya Shimada

Proceedings of the 14th IIAI International Congress on Advanced Applied Informatics, 2023

Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling.

Masanori Hirano, Kentaro Minami, Kentaro Imajo

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

2022

Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction.

Ziyin Liu, Kentaro Minami, Kentaro Imajo

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty.

Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami

Proceedings of the IEEE International Conference on Big Data, 2022

2021

What Data Augmentation Do We Need for Deep-Learning-Based Finance?

Ziyin Liu, Kentaro Minami, Kentaro Imajo

CoRR, 2021

Trader-Company Method: A Metaheuristics for Interpretable Stock Price Prediction.

Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Deep Portfolio Optimization via Distributional Prediction of Residual Factors.

Kentaro Imajo, Kentaro Minami, Katsuya Ito, Kei Nakagawa

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2012

Semi-Supervised Ligand Finding Using Formal Concept Analysis.

Mahito Sugiyama, Kentaro Imajo, Keisuke Otaki, Akihiro Yamamoto

Inf. Media Technol., 2012

Fast Gaussian filtering algorithm using splines.

Kentaro Imajo

Proceedings of the 21st International Conference on Pattern Recognition, 2012

2011

Discovering Ligands for TRP Ion Channels Using Formal Concept Analysis.

Mahito Sugiyama, Kentaro Imajo, Keisuke Otaki, Akihiro Yamamoto

Proceedings of the Latest Advances in Inductive Logic Programming, 2011