4 citations · 4 across the 4 of their papers we have counts for
4 papers
Learning the Optimal Stopping for Early Classification within Finite Horizons via Sequential Probability Ratio Test
Akinori F. Ebihara, Taiki Miyagawa, Kazuyuki Sakurai +1
Time-sensitive machine learning benefits from Sequential Probability Ratio Test (SPRT), which provides an optimal stopping time for early classification of time series. However, in…
Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early Classification
Akinori F. Ebihara, Taiki Miyagawa, Kazuyuki Sakurai +1
Theoretically-inspired sequential density ratio estimation (SDRE) algorithms are proposed for the early classification of time series. Conventional SDRE algorithms can fail to esti…
Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori F. Ebihara, Taiki Miyagawa, Kazuyuki Sakurai +1
Classifying sequential data as early and as accurately as possible is a challenging yet critical problem, especially when a sampling cost is high. One algorithm that achieves this…
Specular- and Diffuse-reflection-based Face Spoofing Detection for Mobile Devices
Akinori F. Ebihara, Kazuyuki Sakurai, Hitoshi Imaoka
In light of the rising demand for biometric-authentication systems, preventing face spoofing attacks is a critical issue for the safe deployment of face recognition systems. Here,…