3 citations · 5 across the 6 of their papers we have counts for
6 papers
Linearizing Binary Optimization Problems Using Variable Posets for Ising Machines
Kentaro Ohno, Nozomu Togawa
Ising machines are next-generation computers expected to efficiently sample near-optimal solutions of combinatorial optimization problems. Combinatorial optimization problems are m…
A Security Verification Framework of Cryptographic Protocols Using Machine Learning
Kentaro Ohno, Misato Nakabayashi
We propose a security verification framework for cryptographic protocols using machine learning. In recent years, as cryptographic protocols have become more complex, research on a…
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks
Kentaro Ohno, Sekitoshi Kanai, Yasutoshi Ida
Gate functions in recurrent models, such as an LSTM and GRU, play a central role in learning various time scales in modeling time series data by using a bounded activation function…
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada +3
This paper proposes a new loss function for adversarial training. Since adversarial training has difficulties, e.g., necessity of high model capacity, focusing on important data po…
Recurrent Neural Networks for Learning Long-term Temporal Dependencies with Reanalysis of Time Scale Representation
Kentaro Ohno, Atsutoshi Kumagai
Recurrent neural networks with a gating mechanism such as an LSTM or GRU are powerful tools to model sequential data. In the mechanism, a forget gate, which was introduced to contr…
On the Effectiveness of Clone Detection for Detecting IoT-related Vulnerable Clones
Kentaro Ohno, Norihiro Yoshida, Wenqing Zhu +1
Since IoT systems provide services over the Internet, they must continue to operate safely even if malicious users attack them. Since the computational resources of edge devices co…