Search Results for author: Yasuharu Koike

Found 4 papers, 0 papers with code

Adaptive sparseness for correntropy-based robust regression via automatic relevance determination

no code implementations31 Jan 2023 Yuanhao Li, Badong Chen, Okito Yamashita, Natsue Yoshimura, Yasuharu Koike

In the present study, regarding the maximum correntropy criterion (MCC) based robust regression algorithm, we investigate to integrate the MCC method with the automatic relevance determination (ARD) technique in a Bayesian framework, so that MCC-based robust regression could be implemented with adaptive sparseness.

Bayesian Inference feature selection +1

Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding

no code implementations20 Jul 2022 Yuanhao Li, Badong Chen, Yuxi Shi, Natsue Yoshimura, Yasuharu Koike

To this end, we introduce the correntropy learning framework into the automatic relevance determination based sparse classification model, proposing a new correntropy-based robust sparse logistic regression algorithm.

Brain Decoding Classification +3

Restricted Minimum Error Entropy Criterion for Robust Classification

no code implementations6 Sep 2019 Yuanhao Li, Badong Chen, Natsue Yoshimura, Yasuharu Koike

The minimum error entropy (MEE) criterion has been verified as a powerful approach for non-Gaussian signal processing and robust machine learning.

Classification Dimensionality Reduction +3

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