52 citations · 176 across the 8 of their papers we have counts for
11 papers
Population structure-learned classifier for high-dimension low-sample-size class-imbalanced problem
Liran Shen, Meng Joo Er, Qingbo Yin
The Classification on high-dimension low-sample-size data (HDLSS) is a challenging problem and it is common to have class-imbalanced data in most application fields. We term this a…
The classification for High-dimension low-sample size data
Liran Shen, Meng Joo Er, Qingbo Yin
Huge amount of applications in various fields, such as gene expression analysis or computer vision, undergo data sets with high-dimensional low-sample-size (HDLSS), which has putte…
Targeted Advertising Based on Browsing History
Yong Zhang, Hongming Zhou, Nganmeng Tan +2
Audience interest, demography, purchase behavior and other possible classifications are ex- tremely important factors to be carefully studied in a targeting campaign. This informat…
Parsimonious Random Vector Functional Link Network for Data Streams
Mahardhika Pratama, Plamen P. Angelov, Edwin Lughofer
The theory of random vector functional link network (RVFLN) has provided a breakthrough in the design of neural networks (NNs) since it conveys solid theoretical justification of r…
A Novel Progressive Multi-label Classifier for Classincremental Data
Mihika Dave, Sahil Tapiawala, Meng Joo Er +1
In this paper, a progressive learning algorithm for multi-label classification to learn new labels while retaining the knowledge of previous labels is designed. New output neurons…
An Online Universal Classifier for Binary, Multi-class and Multi-label Classification
Meng Joo Er, Rajasekar Venkatesan, Ning Wang
Classification involves the learning of the mapping function that associates input samples to corresponding target label. There are two major categories of classification problems:…
A novel online multi-label classifier for high-speed streaming data applications
Rajasekar Venkatesan, Meng Joo Er, Mihika Dave +2
In this paper, a high-speed online neural network classifier based on extreme learning machines for multi-label classification is proposed. In multi-label classification, each of t…
A Novel Progressive Learning Technique for Multi-class Classification
Rajasekar Venkatesan, Meng Joo Er
In this paper, a progressive learning technique for multi-class classification is proposed. This newly developed learning technique is independent of the number of class constraint…
A Novel Online Real-time Classifier for Multi-label Data Streams
Rajasekar Venkatesan, Meng Joo Er, Shiqian Wu +1
In this paper, a novel extreme learning machine based online multi-label classifier for real-time data streams is proposed. Multi-label classification is one of the actively resear…
A High Speed Multi-label Classifier based on Extreme Learning Machines
Meng Joo Er, Rajasekar Venkatesan, Ning Wang
In this paper a high speed neural network classifier based on extreme learning machines for multi-label classification problem is proposed and dis-cussed. Multi-label classificatio…
Multi-Label Classification Method Based on Extreme Learning Machines
Rajasekar Venkatesan, Meng Joo Er
In this paper, an Extreme Learning Machine (ELM) based technique for Multi-label classification problems is proposed and discussed. In multi-label classification, each of the input…