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20182020
most citedAdaptive Initialization Method for K-means Algorithm

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG2020

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…

cs.LG2020

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…

cs.LG20193 cited

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…

eess.SP2018

Effects of Repetitive SSVEPs on EEG Complexity using Multiscale Inherent Fuzzy Entropy

Zehong Cao, Weiping Ding, Yu-Kai Wang +3

Multiscale inherent fuzzy entropy is an objective measurement of electroencephalography (EEG) complexity, reflecting the habituation of brain systems. Entropy dynamics are generall…

cs.HC2018

Dynamically Weighted Ensemble-based Prediction System for Adaptively Modeling Driver Reaction Time

Chun-Hsiang Chuang, Zehong Cao, Po-Tsang Chen +3

Predicting a driver's cognitive state, or more specifically, modeling a driver's reaction time (RT) in response to the appearance of a potential hazard warrants urgent research. In…