Publications

Key Links: Google Scholar | ORCID | ResearchGate

Download BibTex: Source 1| Source 2 |Source 3

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Working Papers

[w18a] DivBoost: Constructing Effective Outlier Ensembles by Base Learner Diversity Maximization

[w19a] HD-Cluster: Synthesized Cluster Analysis and Outlier Detection on High-dimensional Data

Under Review

[w19b] [*Name masked due to double blind review policy]

International Conference on Computer Vision (ICCV), 2019. Submitted, under review.

[w19c] [A new statistical model. *Name masked due to double blind review policy]

AAAI Conference on Artificial Intelligence (AAAI), 2019. Submitted, under review.

I. Peer Reviewed Journal Papers

[j1] PyOD: A Python Toolbox for Scalable Outlier Detection

Yue Zhao, Zain Nasrullah, Zheng Li. Journal of Machine Learning Research (JMLR), 2019.

PDF | JMLR | BibTex | GitHub | Documentation | PyPI

II. Peer Reviewed Conference & Workshop Papers

[c6] Music Artist Classification with Convolutional Recurrent Neural Networks

Zain Nasrullah, Yue Zhao. IEEE International Joint Conference on Neural Networks (IJCNN), 2019, Budapest, Hungary. Accepted, to appear.

PDF for Personal Use | BibTex | GitHub


[c5] LSCP: Locally Selective Combination of Parallel Outlier Ensembles

Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki, Zheng Li. SIAM International Conference on Data Mining (SDM), 2019, Calgary, Canada.

PDF | SIAM Proc| BibTex | Code | Presentation Slides | Poster | Acceptance rate 22.7% (90 / 397 )


[w4] DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles

Yue Zhao, Maciej K. Hryniewicki. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Workshop on Outlier Detection De-constructed (ODD), 2018, London, UK.

PDF | BibTex | Code | Presentation Slides | Poster


[c3] XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning

Yue Zhao, Maciej K. Hryniewicki, IEEE International Joint Conference on Neural Networks (IJCNN), 2018, Rio de Janeiro, Brazil.

PDF for Personal Use | IEEE Xplore | BibTex | Presentation Slides | Code


[c2] Employee Turnover Prediction with Machine Learning: A Reliable Approach

Yue Zhao, Maciej K. Hryniewicki, Francesca Cheng, Boyang Fu, Xiaoyu Zhu. Intelligent System Conference (Intellisys), IEEE, 2018, London, UK.

PDF for Personal Use | SpringerLink | BibTex | Acceptance rate 34% (194 / 568 )


[c1] An Empirical Study of Touch-based Authentication Methods on Smartwatches

Yue Zhao*, Zhongtian Qiu*, Yiqing Yang*, Weiwei Li*, Mingming Fan

(*equal contribution), ACM International Symposium on Wearable Computers (ISWC), 2017, Maui, HI, USA.

PDF | ACM Digital Link | BibTex | Presentation Slides | Acceptance rate 19% (38 / 196 )

III. Technical Reports

[r1] Improve Emergency Department Efficiency by Machine Learning

Yue Zhao*, Liu Yang*

(*equal contribution). University of Toronto, Toronto, Canada, Tech. Report. 2016.

PDF | GitHub