400 citations · 1.6k across the 69 of their papers we have counts for
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Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs
Zihan Liu, Lubin Meng, Xiao Zhang +2
Multiple convolutional neural network (CNN) classifiers have been proposed for electroencephalogram (EEG) based brain-computer interfaces (BCIs). However, CNN models have been foun…
Different Set Domain Adaptation for Brain-Computer Interfaces: A Label Alignment Approach
He He, Dongrui Wu
A brain-computer interface (BCI) system usually needs a long calibration session for each new subject/task to adjust its parameters, which impedes its transition from the laborator…
Discriminative Joint Probability Maximum Mean Discrepancy (DJP-MMD) for Domain Adaptation
Wen Zhang, Dongrui Wu
Maximum mean discrepancy (MMD) has been widely adopted in domain adaptation to measure the discrepancy between the source and target domain distributions. Many existing domain adap…
In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics
Bo Zhang, Yuqi Cui, Meng Wang +3
Tens of millions of women suffer from infertility worldwide each year. In vitro fertilization (IVF) is the best choice for many such patients. However, IVF is expensive, time-consu…
White-Box Target Attack for EEG-Based BCI Regression Problems
Lubin Meng, Chin-Teng Lin, Tzyy-Ring Jung +1
Machine learning has achieved great success in many applications, including electroencephalogram (EEG) based brain-computer interfaces (BCIs). Unfortunately, many machine learning…
Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer Interfaces
Xue Jiang, Xiao Zhang, Dongrui Wu
Deep learning has made significant breakthroughs in many fields, including electroencephalogram (EEG) based brain-computer interfaces (BCIs). However, deep learning models are vuln…
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces
Wen Zhang, Dongrui Wu
Transfer learning makes use of data or knowledge in one problem to help solve a different, yet related, problem. It is particularly useful in brain-computer interfaces (BCIs), for…
EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training
Yuqi Cuui, Yifan Xu, Dongrui Wu
Drowsy driving is pervasive, and also a major cause of traffic accidents. Estimating a driver's drowsiness level by monitoring the electroencephalogram (EEG) signal and taking prev…
Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos
Zihan Liu, Bo Huang, Yuqi Cui +6
Time-lapse is a technology used to record the development of embryos during in-vitro fertilization (IVF). Accurate classification of embryo early development stages can provide emb…
Multi-View Broad Learning System for Primate Oculomotor Decision Decoding
Zhenhua Shi, Xiaomo Chen, Changming Zhao +3
Multi-view learning improves the learning performance by utilizing multi-view data: data collected from multiple sources, or feature sets extracted from the same data source. This…
Optimize TSK Fuzzy Systems for Classification Problems: Mini-Batch Gradient Descent with Uniform Regularization and Batch Normalization
Yuqi Cui, Jian Huang, Dongrui Wu
Takagi-Sugeno-Kang (TSK) fuzzy systems are flexible and interpretable machine learning models; however, they may not be easily optimized when the data size is large, and/or the dat…
Recommendations on Designing Practical Interval Type-2 Fuzzy Systems
Dongrui Wu, Jerry Mendel
Interval type-2 (IT2) fuzzy systems have become increasingly popular in the last 20 years. They have demonstrated superior performance in many applications. However, the operation…
Protecting Privacy of Users in Brain-Computer Interface Applications
Anisha Agarwal, Rafael Dowsley, Nicholas D. McKinney +4
Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference. Among the most in…
Canonical Correlation Analysis (CCA) Based Multi-View Learning: An Overview
Chenfeng Guo, Dongrui Wu
Multi-view learning (MVL) is a strategy for fusing data from different sources or subsets. Canonical correlation analysis (CCA) is very important in MVL, whose main idea is to map…
Patch Learning
Dongrui Wu, Jerry M. Mendel
There have been different strategies to improve the performance of a machine learning model, e.g., increasing the depth, width, and/or nonlinearity of the model, and using ensemble…
Integration of Nonlinear Disturbance Observer within Proxy-based Sliding Mode Control for Pneumatic Muscle Actuators
Yu Cao, Jian Huang, Dongrui Wu +3
This paper presents an integration of nonlinear disturbance observer within proxy-based sliding mode control (IDO-PSMC) approach for Pneumatic Muscle Actuators (PMAs). Due to the n…
On the Vulnerability of CNN Classifiers in EEG-Based BCIs
Xiao Zhang, Dongrui Wu
Deep learning has been successfully used in numerous applications because of its outstanding performance and the ability to avoid manual feature engineering. One such application i…
Active Stacking for Heart Rate Estimation
Dongrui Wu, Feifei Liu, Chengyu Liu
Heart rate estimation from electrocardiogram signals is very important for the early detection of cardiovascular diseases. However, due to large individual differences and varying…
Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis
Cheng Cheng, Beitong Zhou, Guijun Ma +2
The demand of artificial intelligent adoption for condition-based maintenance strategy is astonishingly increased over the past few years. Intelligent fault diagnosis is one critic…
Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA)
Dongrui Wu, Ye Yuan, Yihua Tan
Takagi-Sugeno-Kang (TSK) fuzzy systems are very useful machine learning models for regression problems. However, to our knowledge, there has not existed an efficient and effective…
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…