activity
20192024
most citedRestricted Minimum Error Entropy Criterion for Robust Classification

27 citations · 74 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SP2024★ 4 cited

Sparse Bayesian Correntropy Learning for Robust Muscle Activity Reconstruction from Noisy Brain Recordings

Yuanhao Li, Badong Chen, Natsue Yoshimura +2

Sparse Bayesian learning has promoted many effective frameworks for brain activity decoding, especially for the reconstruction of muscle activity. However, existing sparse Bayesian…

cs.LG2023★ 3 cited

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

Yuanhao Li, Badong Chen, Okito Yamashita +2

Sparseness and robustness are two important properties for many machine learning scenarios. In the present study, regarding the maximum correntropy criterion (MCC) based robust reg…

cs.LG2022★ 9 cited

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

Yuanhao Li, Badong Chen, Yuxi Shi +2

Recent studies have utilized sparse classifications to predict categorical variables from high-dimensional brain activity signals to expose human's intentions and mental states, se…

eess.SP2021★ 3 cited

Partial Maximum Correntropy Regression for Robust Trajectory Decoding from Noisy Epidural Electrocorticographic Signals

Yuanhao Li, Badong Chen, Gang Wang +2

The Partial Least Square Regression (PLSR) exhibits admirable competence for predicting continuous variables from inter-correlated brain recordings in the brain-computer interface.…

physics.data-an2020★ 26 cited

Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses

Paweł Oświęcimka, Stanisław Drożdż, Mattia Frasca +4

The robustness of two widespread multifractal analysis methods, one based on detrended fluctuation analysis and one on wavelet leaders, is discussed in the context of time-series c…

cs.LG2019★ 27 cited

Restricted Minimum Error Entropy Criterion for Robust Classification

Yuanhao Li, Badong Chen, Natsue Yoshimura +1

The minimum error entropy (MEE) criterion has been verified as a powerful approach for non-Gaussian signal processing and robust machine learning. However, the implementation of ME…