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ORCIDYue Zhao 0016
Person information
- affiliation: University of Southern California, CA, USA
- affiliation (former): Carnegie Mellon University, College of Information Systems and Public Policy, Pittsburgh, PA, USA
- affiliation (former): University of Toronto, Canada
Other persons with the same name
- Yue Zhao (aka: Yu'e Zhao) — disambiguation page
- Yue Zhao 0001 — Delft University of Technology, The Netherlands
- Yue Zhao 0002 — INSA de Lyon, France
- Yue Zhao 0003 — Brunel University London, UK
- Yue Zhao 0004
![[0000-0002-5970-5844]](/https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-5970-5844")
— Harbin Institute of Technology, School of Astronautics, Harbin, China - Yue Zhao 0005 — Yunnan University, Institute of Mathematics and Statistics, Kunming, China
- Yue Zhao 0006 — Chinese University of Hong Kong, Department of Information Engineering, CUHK-SenseTime Joint Lab, Hong Kong (and 1 more)
- Yue Zhao 0007 — Stony Brook University, Department of Electrical and Computer Engineering, Stony Brook, NY, USA (and 3 more)
- Yue Zhao 0008 — University of Central Florida, Department of Mathematics, Orlando, FL, USA (and 1 more)
- Yue Zhao 0009 — Qufu Normal University, School of Software, Qufu, China
- Yue Zhao 0010 — Xidian University, State Key Laboratory of Integrated Services Networks, Xidian, China
- Yue Zhao 0011 — North Carolina State University, Department of Computer Science, Raleigh, NC, USA (and 1 more)
- Yue Zhao 0012 — Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, Chongqing, China
- Yue Zhao 0013 — Minzu University of China, School of Information Engineering, Beijing, China
- Yue Zhao 0014 — Shanghai University, School of Computer Engineering and Science, Shanghai, China (and 2 more)
- Yue Zhao 0015 — Southwest Jiaotong University, Provincial Key Lab of Information Coding and Transmission, Chengdu, China
- Yue Zhao 0017 — University of Arkansas, Department of Electrical Engineering, Fayetteville, AR, USA (and 1 more)
- Yue Zhao 0018 — Chinese Academy of Sciences, Institute of Information Engineering, Beijing, China (and 1 more)
- Yue Zhao 0019 — National University of Defense Technology, Science and Technology on Information Systems Engineering Laboratory, Changsha, China
- Yue Zhao 0020 — Beijing Forestry University, School of Technology, Beijing, China (and 1 more)
- Yue Zhao 0021 — Chinese Academy of Sciences, Academy of Mathematics and Systems Science, State Key Laboratory of Scientific and Engineering Computing, Beijing, China
- Yue Zhao 0022 — Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, Beijing, China
- Yue Zhao 0023 — Northwestern Polytechnical University, China
2020 – today
- 2024
[j5]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): 105:1-105:39 (2024)- [c30]Yue Zhao:
Towards Reproducible, Automated, and Scalable Anomaly Detection. AAAI 2024: 22687 - [c29]Yue Zhao, Leman Akoglu:
HPOD: Hyperparameter Optimization for Unsupervised Outlier Detection. AutoML 2024: 2/1-24 - [c28]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c27]Songtao Liu, Hanjun Dai, Yue Zhao, Peng Liu:
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models. ICML 2024 - [c26]Xueying Ding, Yue Zhao, Leman Akoglu:
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. KDD 2024: 585-596 - [c25]Hao Dong, Yue Zhao, Eleni N. Chatzi, Olga Fink:
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities. NeurIPS 2024 - [i46]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i45]Hao Dong, Yue Zhao, Eleni N. Chatzi, Olga Fink:
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities. CoRR abs/2405.17419 (2024) - [i44]Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S. Yu, Kaize Ding, Yue Zhao:
LEGO-Learn: Label-Efficient Graph Open-Set Learning. CoRR abs/2410.16386 (2024) - [i43]Chenxiao Yu, Zhaotian Weng, Yuangang Li, Zheng Li, Xiyang Hu, Yue Zhao:
Towards More Accurate US Presidential Election via Multi-step Reasoning with Large Language Models. CoRR abs/2411.03321 (2024) - [i42]Shawn Li, Huixian Gong, Hao Dong, Tiankai Yang, Zhengzhong Tu, Yue Zhao:
DPU: Dynamic Prototype Updating for Multimodal Out-of-Distribution Detection. CoRR abs/2411.08227 (2024) - [i41]Hanhui Wang, Yihua Zhang, Ruizheng Bai, Yue Zhao, Sijia Liu, Zhengzhong Tu:
Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing. CoRR abs/2411.16832 (2024) - [i40]Junda Wu, Hanjia Lyu, Yu Xia, Zhehao Zhang, Joe Barrow, Ishita Kumar, Mehrnoosh Mirtaheri, Hongjie Chen, Ryan A. Rossi, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, Jiuxiang Gu, Nesreen K. Ahmed, Yu Wang, Xiang Chen, Hanieh Deilamsalehy, Namyong Park, Sungchul Kim, Huanrui Yang, Subrata Mitra, Zhengmian Hu, Nedim Lipka, Dang Nguyen, Yue Zhao, Jiebo Luo, Julian J. McAuley:
Personalized Multimodal Large Language Models: A Survey. CoRR abs/2412.02142 (2024) - [i39]Yuangang Li, Jiaqi Li, Zhuo Xiao, Tiankai Yang, Yi Nian, Xiyang Hu, Yue Zhao:
NLP-ADBench: NLP Anomaly Detection Benchmark. CoRR abs/2412.04784 (2024) - [i38]Jiechao Gao, Yuangang Li, Yue Zhao, Brad Campbell:
H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications. CoRR abs/2412.06210 (2024) - [i37]Lincan Li, Jiaqi Li, Catherine Chen, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun, Lifang He, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao, Swabha Swayamdipta, Willie Neiswanger, Hua Wei, Xiyang Hu, Shixiang Zhu, Tianlong Chen, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong:
Political-LLM: Large Language Models in Political Science. CoRR abs/2412.06864 (2024) - [i36]Tiankai Yang, Yi Nian, Shawn Li, Ruiyao Xu, Yuangang Li, Jiaqi Li, Zhuo Xiao, Xiyang Hu, Ryan A. Rossi, Kaize Ding, Xiaohu You, Yue Zhao:
AD-LLM: Benchmarking Large Language Models for Anomaly Detection. CoRR abs/2412.11142 (2024) - [i35]Sihan Chen, Zhuangzhuang Qian, Wingchun Siu, Xingcan Hu, Jiaqi Li, Shawn Li, Yuehan Qin, Tiankai Yang, Zhuo Xiao, Wanghao Ye, Yichi Zhang, Yushun Dong, Yue Zhao:
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection. CoRR abs/2412.12154 (2024) - [i34]Chenxiao Yu, Zhaotian Weng, Yuangang Li, Zheng Li, Xiyang Hu, Yue Zhao:
A Large-scale Empirical Study on Large Language Models for Election Prediction. CoRR abs/2412.15291 (2024) - 2023
- [j4]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): 19-35 (2023) - [j3]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): 12181-12193 (2023) - [c24]Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann, Ahmed Awadallah:
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels. AAAI 2023: 4937-4945 - [c23]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: 38826-38847 - [c22]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 - [c21]Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) 2023: 254-269 - [i33]Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao:
Weakly Supervised Anomaly Detection: A Survey. CoRR abs/2302.04549 (2023) - [i32]Peng Xu, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqing Yang, Bei Yu:
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks. CoRR abs/2305.14065 (2023) - [i31]Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. CoRR abs/2307.06534 (2023) - [i30]Xueying Ding, Yue Zhao, Leman Akoglu:
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. CoRR abs/2307.10529 (2023) - [i29]Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao:
ADGym: Design Choices for Deep Anomaly Detection. CoRR abs/2309.15376 (2023) - [i28]Hao Dong, Gaëtan Frusque, Yue Zhao, Eleni N. Chatzi, Olga Fink:
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation. CoRR abs/2311.11961 (2023) - [i27]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 abs/2312.14249 (2023) - 2022
- [j2]Yue Zhao, George H. Chen, Zhihao Jia:
TOD: GPU-accelerated Outlier Detection via Tensor Operations. Proc. VLDB Endow. 16(3): 546-560 (2022) - [c20]Yue Zhao, Sean Zhang, Leman Akoglu:
Toward Unsupervised Outlier Model Selection. ICDM 2022: 773-782 - [c19]Songqiao Han, Xiyang Hu, Hailiang Huang, Minqi Jiang, Yue Zhao:
ADBench: Anomaly Detection Benchmark. NeurIPS 2022 - [c18]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. NeurIPS 2022 - [c17]Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, Jundong Li:
Contrastive Attributed Network Anomaly Detection with Data Augmentation. PAKDD (2) 2022: 444-457 - [i26]Zheng Li, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen:
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions. CoRR abs/2201.00382 (2022) - [i25]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 abs/2204.12095 (2022) - [i24]Songqiao Han, Xiyang Hu, Hailiang Huang, Mingqi Jiang, Yue Zhao:
ADBench: Anomaly Detection Benchmark. CoRR abs/2206.09426 (2022) - [i23]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
Benchmarking Node Outlier Detection on Graphs. CoRR abs/2206.10071 (2022) - [i22]Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann, Ahmed Awadallah:
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels. CoRR abs/2208.11290 (2022) - [i21]Yue Zhao, Leman Akoglu:
Towards Unsupervised HPO for Outlier Detection. CoRR abs/2208.11727 (2022) - [i20]Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Ming-Hsuan Yang, Bin Cui:
Diffusion Models: A Comprehensive Survey of Methods and Applications. CoRR abs/2209.00796 (2022) - [i19]Yue Zhao, Sean Zhang, Leman Akoglu:
Toward Unsupervised Outlier Model Selection. CoRR abs/2211.01834 (2022) - 2021
- [c16]Kwei-Herng Lai, Daochen Zha, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Minyang Wan, Diego Martinez, Xia Ben Hu:
TODS: An Automated Time Series Outlier Detection System. AAAI 2021: 16060-16062 - [c15]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 - [c14]Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf H. 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 - [c13]Kwei-Herng Lai, Daochen Zha, Junjie Xu, Yue Zhao, Guanchu Wang, Xia Ben Hu:
Revisiting Time Series Outlier Detection: Definitions and Benchmarks. NeurIPS Datasets and Benchmarks 2021 - [c12]Yue Zhao, Ryan A. Rossi, Leman Akoglu:
Automatic Unsupervised Outlier Model Selection. NeurIPS 2021: 4489-4502 - [i18]Yue Zhao, Zhi Qiao, Cao Xiao, Lucas Glass, Jimeng Sun:
PyHealth: A Python Library for Health Predictive Models. CoRR abs/2101.04209 (2021) - [i17]Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf H. Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik:
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. CoRR abs/2102.09548 (2021) - [i16]Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu:
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice? CoRR abs/2104.01422 (2021) - [i15]Yue Zhao, George H. Chen, Zhihao Jia:
TOD: Tensor-based Outlier Detection. CoRR abs/2110.14007 (2021) - 2020
- [c11]Yue Zhao, Xuejian Wang, Cheng Cheng, Xueying Ding:
Combining Machine Learning Models Using combo Library. AAAI 2020: 13648-13649 - [c10]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: 217-222 - [c9]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: 950-956 - [c8]Zheng Li, Yue Zhao, Jialin Fu:
SynC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources. ICDM (Workshops) 2020: 571-578 - [c7]Zheng Li, Yue Zhao, Nicola Botta, Cezar Ionescu, Xiyang Hu:
COPOD: Copula-Based Outlier Detection. ICDM 2020: 1118-1123 - [c6]Yiqun Mei, Yue Zhao, Wei Liang:
Dsr: An Accurate Single Image Super Resolution Approach For Various Degradations. ICME 2020: 1-6 - [i14]Yue Zhao, Xueying Ding, Jianing Yang, Haoping Bai:
SUOD: Toward Scalable Unsupervised Outlier Detection. CoRR abs/2002.03222 (2020) - [i13]Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Cao Xiao, Yunlong Wang, Jimeng Sun, Leman Akoglu:
SUOD: A Scalable Unsupervised Outlier Detection Framework. CoRR abs/2003.05731 (2020) - [i12]Zheng Li, Yue Zhao, Nicola Botta, Cezar Ionescu, Xiyang Hu:
COPOD: Copula-Based Outlier Detection. CoRR abs/2009.09463 (2020) - [i11]Kwei-Herng Lai, Daochen Zha, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Minyang Wan, Diego Martinez, Xia Ben Hu:
TODS: An Automated Time Series Outlier Detection System. CoRR abs/2009.09822 (2020) - [i10]Yue Zhao, Ryan A. Rossi, Leman Akoglu:
Automating Outlier Detection via Meta-Learning. CoRR abs/2009.10606 (2020) - [i9]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 abs/2011.00447 (2020)
2010 – 2019
- 2019
- [j1]Yue Zhao, Zain Nasrullah, Zheng Li:
PyOD: A Python Toolbox for Scalable Outlier Detection. J. Mach. Learn. Res. 20: 96:1-96:7 (2019) - [c5]Zain Nasrullah, Yue Zhao:
Music Artist Classification with Convolutional Recurrent Neural Networks. IJCNN 2019: 1-8 - [c4]Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki, Zheng Li:
LSCP: Locally Selective Combination in Parallel Outlier Ensembles. SDM 2019: 585-593 - [i8]Yue Zhao, Zain Nasrullah, Zheng Li:
PyOD: A Python Toolbox for Scalable Outlier Detection. CoRR abs/1901.01588 (2019) - [i7]Zain Nasrullah, Yue Zhao:
Music Artist Classification with Convolutional Recurrent Neural Networks. CoRR abs/1901.04555 (2019) - [i6]Colin Wan, Zheng Li, Yue Zhao:
SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula. CoRR abs/1904.07998 (2019) - [i5]Yue Zhao, Xuejian Wang, Cheng Cheng, Xueying Ding:
Combining Machine Learning Models using combo Library. CoRR abs/1910.07988 (2019) - [i4]Yue Zhao, Maciej K. Hryniewicki:
DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles. CoRR abs/1911.10418 (2019) - [i3]Yue Zhao, Maciej K. Hryniewicki:
XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning. CoRR abs/1912.00290 (2019) - 2018
- [c3]Yue Zhao, Maciej K. Hryniewicki:
XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning. IJCNN 2018: 1-8 - [c2]Yue Zhao, Maciej K. Hryniewicki, Francesca Cheng, Boyang Fu, Xiaoyu Zhu:
Employee Turnover Prediction with Machine Learning: A Reliable Approach. IntelliSys (2) 2018: 737-758 - [i2]Yue Zhao, Maciej K. Hryniewicki, Zain Nasrullah, Zheng Li:
LSCP: Locally Selective Combination in Parallel Outlier Ensembles. CoRR abs/1812.01528 (2018) - 2017
- [c1]Yue Zhao, Zhongtian Qiu, Yiqing Yang, Weiwei Li, Mingming Fan:
An empirical study of touch-based authentication methods on smartwatches. ISWC 2017: 122-125 - [i1]Yue Zhao, Zhongtian Qiu, Yiqing Yang, Weiwei Li, Mingming Fan:
An empirical study of touch-based authentication methods on smartwatches. CoRR abs/1710.04608 (2017)
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