Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface

no code implementations • 12 May 2018 • Dongrui Wu, Vernon J. Lawhern, Stephen Gordon, Brent J. Lance, Chin-Teng Lin

Ensemble learning is a powerful approach to construct a strong learner from multiple base learners.

Brain Computer Interface Ensemble Learning +1

Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression

no code implementations • 12 May 2018 • Dongrui Wu, Vernon J. Lawhern, Stephen Gordon, Brent J. Lance, Chin-Teng Lin

There are many important regression problems in real-world brain-computer interface (BCI) applications, e. g., driver drowsiness estimation from EEG signals.

Active Learning Brain Computer Interface +2

EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features

no code implementations • 27 Apr 2017 • Dongrui Wu, Brent J. Lance, Vernon J. Lawhern, Stephen Gordon, Tzyy-Ping Jung, Chin-Teng Lin

Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance.

Brain Computer Interface EEG +1

Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)

no code implementations • 9 Feb 2017 • Dongrui Wu, Vernon J. Lawhern, Stephen Gordon, Brent J. Lance, Chin-Teng Lin

By integrating fuzzy sets with domain adaptation, we propose a novel online weighted adaptation regularization for regression (OwARR) algorithm to reduce the amount of subject-specific calibration data, and also a source domain selection (SDS) approach to save about half of the computational cost of OwARR.

Domain Adaptation EEG +2