449 citations · 1.7k across the 108 of their papers we have counts for
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XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning
Yue Zhao, Maciej K. Hryniewicki
A new semi-supervised ensemble algorithm called XGBOD (Extreme Gradient Boosting Outlier Detection) is proposed, described and demonstrated for the enhanced detection of outliers f…
DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles
Yue Zhao, Maciej K. Hryniewicki
Selecting and combining the outlier scores of different base detectors used within outlier ensembles can be quite challenging in the absence of ground truth. In this paper, an unsu…
Combining Machine Learning Models using combo Library
Yue Zhao, Xuejian Wang, Cheng Cheng +1
Model combination, often regarded as a key sub-field of ensemble learning, has been widely used in both academic research and industry applications. To facilitate this process, we…
LSCP: Locally Selective Combination in Parallel Outlier Ensembles
Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki +1
In unsupervised outlier ensembles, the absence of ground truth makes the combination of base outlier detectors a challenging task. Specifically, existing parallel outlier ensembles…
Music Artist Classification with Convolutional Recurrent Neural Networks
Zain Nasrullah, Yue Zhao
Previous attempts at music artist classification use frame level audio features which summarize frequency content within short intervals of time. Comparatively, more recent music i…
PyOD: A Python Toolbox for Scalable Outlier Detection
Yue Zhao, Zain Nasrullah, Zheng Li
PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data. Uniquely, it provides access to a wide range of outlier detection algorithms,…