論文

• Thien Nguyen Duc, Konstantinos Slavakis. Multilinear kernel regression and imputation via manifold learning, IEEE Open Journal of Signal Processing, IEEE, vol. 5, pp. 1073-1088, Aug. 2024.
• Ye Chen, Kyohei Okubo, Konstantinos Slavakis, Yoshitaka Kitamot. Estimation of biomolecule amount by analyzing magnetic nanoparticle cluster distributions from alternating current magnetization spectra for magnetic biosensing, Journal of Magnetism and Magnetic Materials, Elsevier, Vol. 588, 171387, Oct. 2023.  公式リンク  
  
• K. Slavakis, G. N. Shetty, L. Cannelli, G. Scutari, U. Nakarmi, L. Ying. Kernel regression imputation in manifolds via bi-linear modeling: The dynamic-MRI case, IEEE Transactions on Computational Imaging, IEEE, vol. 8, pp. 133-147, Feb. 2022.

国際会議発表 (査読有り)

• Duc Thien Nguyen, Konstantinos Slavakis. Multilinear kernel regression and imputation via manifold learning: The dynamic MRI case, IEEE International Conference on Acoustics, Speech and Signal Processing, Mar. 2024.  公式リンク  
  
• Yuki Akiyama, Konstantinos Slavakis. Proximal Bellman mappings for reinforcement learning and their application to robust adaptive filtering, IEEE International Conference on Acoustics, Speech and Signal Processing, Mar. 2024.  公式リンク  
  
• Ye Chen, Kyohei Okubo, Konstantinos Slavakis, Yoshitaka Kitamoto. A machine-learning-based analysis method of AC magnetization spectra for estimating cluster distribution of magnetic nanoparticles, IEEE International Magnetics Conference (INTERMAG), May 2023.
• M. Vu, Y. Akiyama, K. Slavakis. Dynamic selection of p-norm in linear adaptive filtering via online kernel-based reinforcement learning, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2023.  公式リンク  
  
• Ye Chen, Konstantinos Slavakis, Yoshitaka Kitamoto. A Machine Learning Based Analysis Method of AC Magnetization Spectra of Magnetic Nanoparticles and Its Application to Magnetic Biosensing, ICFPM2022 International Conference on Fine Particle Magnetism, Oct. 2022.
• C. Ye, K. Slavakis, J. Nakuci, S. F. Muldoon, J. Medaglia. Online classification of dynamic multilayer-network time series in Riemannian manifolds, Internations Conference Acoustics, Speech and Signal Processing, pp. 3815-3819, May 2021.
• K. Slavakis, M. Yukawa. Outlier-robust kernel hierarchical-optimization RLS on a budget with affine constraints, International Conference Acoustics, Speech and Signal Processing, pp. 5335-5339, May 2021.

国内会議発表 (査読なし・不明)

• SLAVAKIS KONSTANTINOS. New Nonparametric Bellman mappings for reinforcement learning, 電子情報通信学会, Sept. 2024.
• Yuki Akiyama, Konstantinos Slavakis. Proximal Bellman mappings for robust adaptive filtering, Signal Processing (SIP) Symposium, Nov. 2023.
• Duc Thien Nguyen, Konstantinos Slavakis. Multi-linear kernel regression and imputation in data manifolds, Signal Processing (SIP) Symposium, Nov. 2023.
• Yuki Akiyama, Konstantinos Slavakis. Distributed reinforcement learning via proximal Bellman mappings, Signal Processing (SIP) Symposium, Nov. 2023.
• M. Vu, Y. Akiyama, K. Slavakis. Least-mean p-norm adaptive filtering via reinforcement learning, Signal Processing (SIP) Symposium, Nov. 2022.
• Y. Akiyama, M. Vu, K. Slavakis. Online lightweight reinforcement learning against outliers in linear adaptive filtering, Signal Processing (SIP) Symposium, Nov. 2022.
• K. Slavakis. Learning from data in manifolds: Methods, applications, and recent developments, Signal Processing (SIP) Symposium, IEICE, Nov. 2021.

その他の論文・著書など

• Thien Nguyen Duc, Konstantinos Slavakis. Multi-linear kernel regression and imputation in data manifolds, Apr. 2023.

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