2 citations · 4 across the 8 of their papers we have counts for
5 papers · 1 filter
Mitigating shortage of labeled data using clustering-based active learning with diversity exploration
Xuyang Yan, Shabnam Nazmi, Biniam Gebru +4
In this paper, we proposed a new clustering-based active learning framework, namely Active Learning using a Clustering-based Sampling (ALCS), to address the shortage of labeled dat…
A Supervised Feature Selection Method For Mixed-Type Data using Density-based Feature Clustering
Xuyang Yan, Mrinmoy Sarkar, Biniam Gebru +2
Feature selection methods are widely used to address the high computational overheads and curse of dimensionality in classifying high-dimensional data. Most conventional feature se…
A Clustering-based Framework for Classifying Data Streams
Xuyang Yan, Abdollah Homaifar, Mrinmoy Sarkar +2
The non-stationary nature of data streams strongly challenges traditional machine learning techniques. Although some solutions have been proposed to extend traditional machine lear…
Evolving Multi-label Classification Rules by Exploiting High-order Label Correlation
Shabnam Nazmi, Xuyang Yan, Abdollah Homaifar +1
In multi-label classification tasks, each problem instance is associated with multiple classes simultaneously. In such settings, the correlation between labels contains valuable in…
Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural Network
Abenezer Girma, Xuyang Yan, Abdollah Homaifar
Despite advancements in vehicle security systems, over the last decade, auto-theft rates have increased, and cyber-security attacks on internet-connected and autonomous vehicles ar…