Publications

SUOD: Accelerating Large-scale Unsupervised Heterogeneous Outlier Detection

Outlier detection (OD) is a key data mining task for identifying abnormal objects from general samples with numerous high-stake …

COPOD: Copula-Based Outlier Detection

Outlier detection refers to the identification of rare items that are deviant from the general data distribution. Existing unsupervised …

SynC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources

A synthetic dataset is a data object that is generated programmatically, and it may be valuable to creating a single dataset from …

DSR: An Accurate Single Image Super Resolution Approach for Various Degradations

Recently, convolution neural networks based approaches have achieved unprecedented success for image super resolution. However, such …

SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula

Synthetic population generation is the process of combining multiple socioeonomic and demographic datasets from various sources and at …

Combining Machine Learning Models Using combo Library

Model combination, often regarded as a key sub-field of ensemble learning, has been widely used in both academic research and industry …

PyOD: A Python Toolbox for Scalable Outlier Detection

PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data. Uniquely, it provides access to a …

Music Artist Classification with Convolutional Recurrent Neural Networks

Previous attempts at music artist classification use frame level audio features which summarize frequency content within short …

LSCP: Locally Selective Combination in Parallel Outlier Ensembles

In unsupervised outlier ensembles, the absence of ground truth makes the combination of base outlier detectors a challenging task. …

XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning

A new semi-supervised ensemble algorithm called XGBOD (Extreme Gradient Boosting Outlier Detection) is proposed, described and …

Employee Turnover Prediction with Machine Learning: A Reliable Approach

Supervised machine learning methods are described, demonstrated and assessed for the prediction of employee turnover within an …

An empirical study of touch-based authentication methods on smartwatches

The emergence of smartwatches poses new challenges to information security. Although there are mature touch-based authentication …