135 citations · 167 across the 8 of their papers we have counts for
8 papers
User Identity Protection in EEG-based Brain-Computer Interfaces
L. Meng, X. Jiang, J. Huang +3
A brain-computer interface (BCI) establishes a direct communication pathway between the brain and an external device. Electroencephalogram (EEG) is the most popular input signal in…
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks
Lubin Meng, Jian Huang, Zhigang Zeng +6
Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to deeper understanding of the brain and wide adopti…
Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline
Dongrui Wu, Xue Jiang, Ruimin Peng +3
Transfer learning (TL) has been widely used in motor imagery (MI) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promis…
BoostTree and BoostForest for Ensemble Learning
Changming Zhao, Dongrui Wu, Jian Huang +4
Bootstrap aggregating (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite model for more accurate and…
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality Reduction
Zhenhua Shi, Dongrui Wu, Jian Huang +2
Dimensionality reduction is an important operation in information visualization, feature extraction, clustering, regression, and classification, especially for processing noisy hig…
On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression
Dongrui Wu, Chin-Teng Lin, Jian Huang +1
Fuzzy systems have achieved great success in numerous applications. However, there are still many challenges in designing an optimal fuzzy system, e.g., how to efficiently optimize…
Active Learning for Regression Using Greedy Sampling
Dongrui Wu, Chin-Teng Lin, Jian Huang
Regression problems are pervasive in real-world applications. Generally a substantial amount of labeled samples are needed to build a regression model with good generalization abil…
Affect Estimation in 3D Space Using Multi-Task Active Learning for Regression
Dongrui Wu, Jian Huang
Acquisition of labeled training samples for affective computing is usually costly and time-consuming, as affects are intrinsically subjective, subtle and uncertain, and hence multi…