Kentaro Ohno

According to our database, Kentaro Ohno authored at least 10 papers between 2021 and 2024.

Collaborative distances:

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

2024

Giving a Quasi-Initial Solution to Ising Machines by Controlling External Magnetic Field Coefficients.

Soma Kawakami, Kentaro Ohno, Dema Ba, Satoshi Yagi, Junji Teramoto, Nozomu Togawa

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., January, 2024

Toward Practical Benchmarks of Ising Machines: A Case Study on the Quadratic Knapsack Problem.

Kentaro Ohno, Tatsuhiko Shirai, Nozomu Togawa

IEEE Access, 2024

An Interaction Coefficient Control Method for Setting Initial Solutions to Ising Machines.

Soma Kawakami, Kentaro Ohno, Dema Ba, Satoshi Yagi, Junji Teramoto, Nozomu Togawa

Proceedings of the IEEE International Conference on Consumer Electronics, 2024

2023

Linearization via Ordering Variables in Binary Optimization for Ising Machines.

Kentaro Ohno, Nozomu Togawa

CoRR, 2023

A Security Verification Framework of Cryptographic Protocols Using Machine Learning.

Kentaro Ohno, Misato Nakabayashi

CoRR, 2023

One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training.

Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Kentaro Ohno, Yasutoshi Ida

Proceedings of the International Conference on Machine Learning, 2023

A Quasi-Initial Solution Giving Method for Ising Machines by Controlling External Magnetic Field Coefficients.

Soma Kawakami, Kentaro Ohno, Dema Ba, Satoshi Yagi, Junji Teramoto, Nozomu Togawa

Proceedings of the IEEE International Conference on Consumer Electronics, 2023

Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks.

Kentaro Ohno, Sekitoshi Kanai, Yasutoshi Ida

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

On the Effectiveness of Clone Detection for Detecting IoT-related Vulnerable Clones.

Kentaro Ohno, Norihiro Yoshida, Wenqing Zhu, Hiroaki Takada

CoRR, 2021

Recurrent Neural Networks for Learning Long-term Temporal Dependencies with Reanalysis of Time Scale Representation.

Kentaro Ohno, Atsutoshi Kumagai

Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021