Yue Zhao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 52

Top Topics

Distribution Function

Corneal Endothelium

Outlier Detection

Model Selection

Top Venues

Publications

Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, Ming-Hsuan Yang
Diffusion Models: A Comprehensive Survey of Methods and Applications. ACM Comput. Surv. 56 (4) (2024)
Xueying Ding, Yue Zhao, Leman Akoglu
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. KDD (2024)
Xueying Ding, Yue Zhao, Leman Akoglu
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. CoRR (2023)
Zheng Li, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions. IEEE Trans. Knowl. Data Eng. 35 (12) (2023)
Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann, Ahmed Hassan Awadallah
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels. AAAI (2023)
Yingzhou Lu, Minjie Shen, Yue Zhao, Chenhao Li, Fan Meng, Xiao Wang, David M. Herrington, Yue Wang, Tim Fu, Capucine Van Rechem
GenoCraft: A Comprehensive, User-Friendly Web-Based Platform for High-Throughput Omics Data Analysis and Visualization. CoRR (2023)
Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao
ADGym: Design Choices for Deep Anomaly Detection. NeurIPS (2023)
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. CoRR (2023)
Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu
The Need for Unsupervised Outlier Model Selection: A Review and Evaluation of Internal Evaluation Strategies. SIGKDD Explor. 25 (1) (2023)
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) (2023)
Peng Xu, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks. ICML (2023)
Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao
ADGym: Design Choices for Deep Anomaly Detection. CoRR (2023)
Songqiao Han, Xiyang Hu, Hailiang Huang, Minqi Jiang, Yue Zhao
ADBench: Anomaly Detection Benchmark. NeurIPS (2022)
Yue Zhao, Sean Zhang, Leman Akoglu
Toward Unsupervised Outlier Model Selection. ICDM (2022)
Yue Zhao, Leman Akoglu
Towards Unsupervised HPO for Outlier Detection. CoRR (2022)
Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, Jundong Li
Contrastive Attributed Network Anomaly Detection with Data Augmentation. PAKDD (2) (2022)
Zheng Li, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions. CoRR (2022)
Yue Zhao, Sean Zhang, Leman Akoglu
Toward Unsupervised Outlier Model Selection. CoRR (2022)
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu
PyGOD: A Python Library for Graph Outlier Detection. CoRR (2022)
Songqiao Han, Xiyang Hu, Hailiang Huang, Mingqi Jiang, Yue Zhao
ADBench: Anomaly Detection Benchmark. CoRR (2022)
Yue Zhao, George H. Chen, Zhihao Jia
TOD: Tensor-based Outlier Detection. CoRR (2021)
Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection. MLSys (2021)
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. CoRR (2021)
Yue Zhao, Zhi Qiao, Cao Xiao, Lucas Glass, Jimeng Sun
PyHealth: A Python Library for Health Predictive Models. CoRR (2021)
Yue Zhao, Ryan A. Rossi, Leman Akoglu
Automatic Unsupervised Outlier Model Selection. NeurIPS (2021)
Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice? CoRR (2021)
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. NeurIPS Datasets and Benchmarks (2021)
Changlin Wan, Dongya Jia, Yue Zhao, Wennan Chang, Sha Cao, Xiao Wang, Chi Zhang
A data denoising approach to optimize functional clustering of single cell RNA-sequencing data. BIBM (2020)
Yue Zhao, Xuejian Wang, Cheng Cheng, Xueying Ding
Combining Machine Learning Models Using combo Library. AAAI (2020)
Zheng Li, Yue Zhao, Jialin Fu
SynC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources. ICDM (Workshops) (2020)
Zheng Li, Yue Zhao, Nicola Botta, Cezar Ionescu, Xiyang Hu
COPOD: Copula-Based Outlier Detection. CoRR (2020)
Yue Zhao, Ryan A. Rossi, Leman Akoglu
Automating Outlier Detection via Meta-Learning. CoRR (2020)
Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Cao Xiao, Yunlong Wang, Jimeng Sun, Leman Akoglu
SUOD: A Scalable Unsupervised Outlier Detection Framework. CoRR (2020)
Yiqun Mei, Yue Zhao, Wei Liang
Dsr: An Accurate Single Image Super Resolution Approach For Various Degradations. ICME (2020)
Yue Zhao, Xueying Ding, Jianing Yang, Haoping Bai
SUOD: Toward Scalable Unsupervised Outlier Detection. CoRR (2020)
Meng-Chieh Lee, Yue Zhao, Aluna Wang, Pierre Jinghong Liang, Leman Akoglu, Vincent S. Tseng, Christos Faloutsos
AutoAudit: Mining Accounting and Time-Evolving Graphs. CoRR (2020)
Zheng Li, Yue Zhao, Nicola Botta, Cezar Ionescu, Xiyang Hu
COPOD: Copula-Based Outlier Detection. ICDM (2020)
Meng-Chieh Lee, Yue Zhao, Aluna Wang, Pierre Jinghong Liang, Leman Akoglu, Vincent S. Tseng, Christos Faloutsos
AutoAudit: Mining Accounting and Time-Evolving Graphs. IEEE BigData (2020)
Yue Zhao, Zain Nasrullah, Zheng Li
PyOD: A Python Toolbox for Scalable Outlier Detection. CoRR (2019)
Zain Nasrullah, Yue Zhao
Music Artist Classification with Convolutional Recurrent Neural Networks. IJCNN (2019)
Yue Zhao, Zain Nasrullah, Zheng Li
PyOD: A Python Toolbox for Scalable Outlier Detection. J. Mach. Learn. Res. 20 (2019)
Yue Zhao, Xuejian Wang, Cheng Cheng, Xueying Ding
Combining Machine Learning Models using combo Library. CoRR (2019)
Yue Zhao, Maciej K. Hryniewicki
DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles. CoRR (2019)
Zain Nasrullah, Yue Zhao
Music Artist Classification with Convolutional Recurrent Neural Networks. CoRR (2019)
Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki, Zheng Li
LSCP: Locally Selective Combination in Parallel Outlier Ensembles. SDM (2019)
Yue Zhao, Maciej K. Hryniewicki
XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning. CoRR (2019)
Colin Wan, Zheng Li, Yue Zhao
SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula. CoRR (2019)
Yue Zhao, Maciej K. Hryniewicki, Francesca Cheng, Boyang Fu, Xiaoyu Zhu
Employee Turnover Prediction with Machine Learning: A Reliable Approach. IntelliSys (2) (2018)
Yue Zhao, Maciej K. Hryniewicki
XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning. IJCNN (2018)
Yue Zhao, Maciej K. Hryniewicki, Zain Nasrullah, Zheng Li
LSCP: Locally Selective Combination in Parallel Outlier Ensembles. CoRR (2018)
Yue Zhao, Zhongtian Qiu, Yiqing Yang, Weiwei Li, Mingming Fan
An empirical study of touch-based authentication methods on smartwatches. ISWC (2017)
Yue Zhao, Zhongtian Qiu, Yiqing Yang, Weiwei Li, Mingming Fan
An empirical study of touch-based authentication methods on smartwatches. CoRR (2017)