142 citations · 707 across the 24 of their papers we have counts for
10 papers · 1 filter
EnK: Encoding time-information in convolution
Avinash Kumar Singh, Chin-Teng Lin
Recent development in deep learning techniques has attracted attention in decoding and classification in EEG signals. Despite several efforts utilizing different features of EEG si…
Clustering via torque balance with mass and distance
Jie Yang, Chin-Teng Lin
Grouping similar objects is a fundamental tool of scientific analysis, ubiquitous in disciplines from biology and chemistry to astronomy and pattern recognition. Inspired by the to…
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…
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning
Yurui Ming, Dongrui Wu, Yu-Kai Wang +2
Fatigue is the most vital factor of road fatalities and one manifestation of fatigue during driving is drowsiness. In this paper, we propose using deep Q-learning to analyze an ele…
Adaptive Initialization Method for K-means Algorithm
Jie Yang, Yu-Kai Wang, Xin Yao +1
The K-means algorithm is a widely used clustering algorithm that offers simplicity and efficiency. However, the traditional K-means algorithm uses the random method to determine th…
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…
Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
Ensemble learning is a powerful approach to construct a strong learner from multiple base learners. The most popular way to aggregate an ensemble of classifiers is majority voting,…
Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
There are many important regression problems in real-world brain-computer interface (BCI) applications, e.g., driver drowsiness estimation from EEG signals. This paper considers of…
Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
One big challenge that hinders the transition of brain-computer interfaces (BCIs) from laboratory settings to real-life applications is the availability of high-performance and rob…