research
∙
04/01/2023
Doubly Stochastic Models: Learning with Unbiased Label Noises and Inference Stability
Random label noises (or observational noises) widely exist in practical ...
share
research
∙
11/28/2022
Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces
Machine learning has achieved great success in electroencephalogram (EEG...
research
∙
07/20/2022
Facial Affect Analysis: Learning from Synthetic Data Multi-Task Learning Challenges
Facial affect analysis remains a challenging task with its setting trans...
research
∙
06/07/2022
PyTSK: A Python Toolbox for TSK Fuzzy Systems
This paper presents PyTSK, a Python toolbox for developing Takagi-Sugeno...
research
∙
10/07/2021
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow
Principal component analysis (PCA) has been widely used as an effective ...
research
∙
10/06/2021
Exploring the Common Principal Subspace of Deep Features in Neural Networks
We find that different Deep Neural Networks (DNNs) trained with the same...
research
∙
02/08/2021
Curse of Dimensionality for TSK Fuzzy Neural Networks: Explanation and Solutions
Takagi-Sugeno-Kang (TSK) fuzzy system with Gaussian membership functions...
research
∙
02/04/2021
Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review
Physiological computing uses human physiological data as system inputs i...
research
∙
11/30/2020
FCM-RDpA: TSK Fuzzy Regression Model Construction Using Fuzzy C-Means Clustering, Regularization, DropRule, and Powerball AdaBelief
To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regre...
research
∙
10/30/2020
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks
Research and development of electroencephalogram (EEG) based brain-compu...
research
∙
09/02/2020
Overcoming Negative Transfer: A Survey
Transfer learning aims to help the target task with little or no trainin...
research
∙
07/03/2020
Transfer Learning for Brain-Computer Interfaces: A Complete Pipeline
Transfer learning (TL) has been widely used in electroencephalogram (EEG...
research
∙
04/29/2020
Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs
Over-parameterized deep neural networks (DNNs) with sufficient capacity ...
research
∙
04/13/2020
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016
A brain-computer interface (BCI) enables a user to communicate with a co...
research
∙
04/13/2020
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progresses Since 2016
A brain-computer interface (BCI) enables a user to communicate directly ...
research
∙
03/01/2020
MBGD-RDA Training and Rule Pruning for Concise TSK Fuzzy Regression Models
To effectively train Takagi-Sugeno-Kang (TSK) fuzzy systems for regressi...
research
∙
02/27/2020
Supervised Enhanced Soft Subspace Clustering (SESSC) for TSK Fuzzy Classifiers
Fuzzy c-means based clustering algorithms are frequently used for Takagi...
research
∙
01/30/2020
Tiny Noise Can Make an EEG-Based Brain-Computer Interface Speller Output Anything
An electroencephalogram (EEG) based brain-computer interface (BCI) spell...
research
∙
01/28/2020
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications
Brain-Computer Interface (BCI) is a powerful communication tool between ...
research
∙
01/14/2020
Unsupervised Pool-Based Active Learning for Linear Regression
In many real-world machine learning applications, unlabeled data can be ...
research
∙
01/09/2020
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality Reduction
Dimensionality reduction is an important operation in information visual...
research
∙
01/08/2020
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning
Fatigue is the most vital factor of road fatalities and one manifestatio...
research
∙
01/04/2020
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks
A deep neural network (DNN) with piecewise linear activations can partit...
research
∙
12/03/2019
Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs
Multiple convolutional neural network (CNN) classifiers have been propos...
research
∙
12/03/2019
Different Set Domain Adaptation for Brain-Computer Interfaces: A Label Alignment Approach
A brain-computer interface (BCI) system usually needs a long calibration...
research
∙
12/03/2019
Heterogeneous Label Space Transfer Learning for Brain-Computer Interfaces: A Label Alignment Approach
A brain-computer interface (BCI) system usually needs a long calibration...
research
∙
12/01/2019
Transferability versus Discriminability: Joint Probability Distribution Adaptation (JPDA)
Transfer learning makes use of data or knowledge in one task to help sol...
research
∙
11/10/2019
In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics
Tens of millions of women suffer from infertility worldwide each year. I...
research
∙
11/07/2019
Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer Interfaces
Deep learning has made significant breakthroughs in many fields, includi...
research
∙
11/07/2019
White-Box Target Attack for EEG-Based BCI Regression Problems
Machine learning has achieved great success in many applications, includ...
research
∙
10/14/2019
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces
Transfer learning makes use of data or knowledge in one problem to help ...
research
∙
09/25/2019
EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training
Drowsy driving is pervasive, and also a major cause of traffic accidents...
research
∙
08/22/2019
Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos
Time-lapse is a technology used to record the development of embryos dur...
research
∙
08/16/2019
Multi-View Broad Learning System for Primate Oculomotor Decision Decoding
Multi-view learning improves the learning performance by utilizing multi...
research
∙
08/01/2019
Optimize TSK Fuzzy Systems for Big Data Classification Problems: Bag of Tricks
Takagi-Sugeno-Kang (TSK) fuzzy systems are flexible and interpretable ma...
research
∙
07/03/2019
Recommendations on Designing Practical Interval Type-2 Fuzzy Systems
Interval type-2 (IT2) fuzzy systems have become increasingly popular in ...
research
∙
07/03/2019
Canonical Correlation Analysis (CCA) Based Multi-View Learning: An Overview
Multi-view learning (MVL) is a strategy for fusing data from different s...
research
∙
07/02/2019
Protecting Privacy of Users in Brain-Computer Interface Applications
Machine learning (ML) is revolutionizing research and industry. Many ML ...
research
∙
06/01/2019
Patch Learning
There have been different strategies to improve the performance of a mac...
research
∙
03/31/2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs
Deep learning has been successfully used in numerous applications becaus...
research
∙
03/26/2019
Optimize TSK Fuzzy Systems for Big Data Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA)
Takagi-Sugeno-Kang (TSK) fuzzy systems are very useful machine learning ...
research
∙
03/26/2019
Active Stacking for Heart Rate Estimation
Heart rate estimation from electrocardiogram signals is very important f...
research
∙
03/25/2019
On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression
Fuzzy systems have achieved great success in numerous applications. Howe...
research
∙
12/15/2018
Multi-Tasking Evolutionary Algorithm (MTEA) for Single-Objective Continuous Optimization
Multi-task learning uses auxiliary data or knowledge from relevant tasks...
research
∙
08/08/2018
Transfer Learning for Brain-Computer Interfaces: An Euclidean Space Data Alignment Approach
Almost all EEG-based brain-computer interfaces (BCIs) need some labeled ...
research
∙
08/08/2018
EEG-Based Driver Drowsiness Estimation Using Convolutional Neural Networks
Deep learning, including convolutional neural networks (CNNs), has start...
research
∙
08/08/2018
Transfer Learning Enhanced Common Spatial Pattern Filtering for Brain Computer Interfaces (BCIs): Overview and a New Approach
The electroencephalogram (EEG) is the most widely used input for brain c...
research
∙
08/08/2018
Real-time fMRI-based Brain Computer Interface: A Review
In recent years, the rapid development of neuroimaging technology has be...
research
∙
08/08/2018
Affect Estimation in 3D Space Using Multi-Task Active Learning for Regression
Acquisition of labeled training samples for affective computing is usual...
research
∙
08/08/2018