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ORCIDYe Zhu 0002
Person information
- unicode name: 祝烨
- affiliation: Deakin University, School of Information Technology, Burwood, VIC, Australia
- affiliation (PhD 2017): Monash University, Faculty of Information Technology, Clayton, VIC, Australia
Other persons with the same name
- Ye Zhu — disambiguation page
- Ye Zhu 0001
![[0000-0001-6459-204X]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-6459-204X")
— Cleveland State University, Department of Electrical Engineering and Computer Science, OH, USA (and 1 more) - Ye Zhu 0003 — South China University of Technology, School of Computer Science and Engineering, Guangzhou , China
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Books and Theses
- 2017
[b1]Ye Zhu:
Efficient Identification of Arbitrarily Shaped and Varied Density Clusters in High-dimensional Data. Monash University, Australia, 2017
Journal Articles
- 2024
- [j40]Chenquan Gan, Xiang Fu, Qingdong Feng, Qingyi Zhu, Yang Cao, Ye Zhu:
A multimodal fusion network with attention mechanisms for visual-textual sentiment analysis. Expert Syst. Appl. 242: 122731 (2024) - [j39]Yang Cao, Shiva Raj Pokhrel, Ye Zhu, Robin Doss, Gang Li:
Automation and Orchestration of Zero Trust Architecture: Potential Solutions and Challenges. Mach. Intell. Res. 21(2): 294-317 (2024) - [j38]Chen Li, Yang Cao, Ye Zhu, Debo Cheng, Chengyuan Li, Yasuhiko Morimoto:
Ripple Knowledge Graph Convolutional Networks for Recommendation Systems. Mach. Intell. Res. 21(3): 481-494 (2024) - [j37]Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Luxing Yang, Gang Li:
Detecting Change Intervals with Isolation Distributional Kernel. J. Artif. Intell. Res. 79: 273-306 (2024) - [j36]Kaifan Huang, Xiaofan Yang, Lu-Xing Yang, Ye Zhu, Gang Li:
Mitigating the Impact of a False Message Through Sequential Release of Clarifying Messages. IEEE Trans. Netw. Sci. Eng. 11(2): 1785-1798 (2024) - [j35]Kai Ming Ting, Zongyou Liu, Lei Gong, Hang Zhang, Ye Zhu:
A new distributional treatment for time series anomaly detection. VLDB J. 33(3): 753-780 (2024) - 2023
- [j34]Junhao Xiao, Chenquan Gan, Qingyi Zhu, Ye Zhu, Gang Liu:
CFNet: Facial expression recognition via constraint fusion under multi-task joint learning network. Appl. Soft Comput. 141: 110312 (2023) - [j33]Chenquan Gan, Anqi Liu, Qingyi Zhu, Ye Zhu, Yong Xiang, Jun Liu:
Social tie-driven coupling propagation of user awareness and information in Device-to-Device communications. Comput. Networks 237: 110087 (2023) - [j32]Moting Su, Wenjie Zhao, Ye Zhu, Donglan Zha, Yushu Zhang, Peng Xu:
Anomaly detection of vectorized time series on aircraft battery data. Expert Syst. Appl. 227: 120219 (2023) - [j31]Ye Zhu, Kai Ming Ting:
Kernel-based clustering via Isolation Distributional Kernel. Inf. Syst. 117: 102212 (2023) - [j30]Mathew Zuparic, Sergiy Shelyag, Maia Angelova, Ye Zhu, Alexander C. Kalloniatis:
Modelling host population support for combat adversaries. J. Oper. Res. Soc. 74(3): 928-943 (2023) - [j29]Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang, Ye Zhu:
Isolation Kernel Estimators. Knowl. Inf. Syst. 65(2): 759-787 (2023) - [j28]Xin Han, Ye Zhu, Kai Ming Ting, Gang Li:
The impact of isolation kernel on agglomerative hierarchical clustering algorithms. Pattern Recognit. 139: 109517 (2023) - [j27]Kai Ming Ting, Jonathan R. Wells, Ye Zhu:
Point-Set Kernel Clustering. IEEE Trans. Knowl. Data Eng. 35(5): 5147-5158 (2023) - [j26]Lu Zhou, Ye Zhu, Yong Xiang, Tianrui Zong:
A novel feature-based framework enabling multi-type DDoS attacks detection. World Wide Web (WWW) 26(1): 163-185 (2023) - [j25]Man Li, Ye Zhu, Yuxin Shen, Maia Angelova:
Clustering-enhanced stock price prediction using deep learning. World Wide Web (WWW) 26(1): 207-232 (2023) - 2022
- [j24]Lu Zhou, Ye Zhu, Tianrui Zong, Yong Xiang:
A feature selection-based method for DDoS attack flow classification. Future Gener. Comput. Syst. 132: 67-79 (2022) - [j23]Man Li, Ye Zhu, Taige Zhao, Maia Angelova:
Weighted dynamic time warping for traffic flow clustering. Neurocomputing 472: 266-279 (2022) - [j22]Ye Zhu, Kai Ming Ting, Yuan Jin, Maia Angelova:
Hierarchical clustering that takes advantage of both density-peak and density-connectivity. Inf. Syst. 103: 101871 (2022) - [j21]Ye Zhu, Ruoyu Zhao, Yushu Zhang, Xiangli Xiao, Rushi Lan, Yong Xiang:
Noise-free thumbnail-preserving image encryption based on MSB prediction. Inf. Sci. 617: 395-415 (2022) - [j20]Kai Ming Ting, Zongyou Liu, Hang Zhang, Ye Zhu:
A New Distributional Treatment for Time Series and An Anomaly Detection Investigation. Proc. VLDB Endow. 15(11): 2321-2333 (2022) - 2021
- [j19]Mathew Zuparic, Maia Angelova, Ye Zhu, Alexander C. Kalloniatis:
Adversarial decision strategies in multiple network phased oscillators: The Blue-Green-Red Kuramoto-Sakaguchi model. Commun. Nonlinear Sci. Numer. Simul. 95: 105642 (2021) - [j18]Ye Zhu, Kai Ming Ting:
Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel. J. Artif. Intell. Res. 71: 667-695 (2021) - [j17]Ye Zhu, Kai Ming Ting, Mark J. Carman, Maia Angelova:
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities. Pattern Recognit. 117: 107977 (2021) - [j16]Wenjie Zhao, Yushu Zhang, Ye Zhu, Peng Xu:
Anomaly detection of aircraft lead-acid battery. Qual. Reliab. Eng. Int. 37(3): 1186-1197 (2021) - 2020
- [j15]Maia Angelova, Chandan K. Karmakar, Ye Zhu, Sean P. A. Drummond, Jason Ellis:
Automated Method for Detecting Acute Insomnia Using Multi-Night Actigraphy Data. IEEE Access 8: 74413-74422 (2020) - [j14]Shitanshu Kusmakar, Sergiy Shelyag, Ye Zhu, Dan Dwyer, Paul B. Gastin, Maia Angelova:
Machine Learning Enabled Team Performance Analysis in the Dynamical Environment of Soccer. IEEE Access 8: 90266-90279 (2020) - [j13]Yuan Jin, Mark J. Carman, Ye Zhu, Yong Xiang:
A technical survey on statistical modelling and design methods for crowdsourcing quality control. Artif. Intell. 287: 103351 (2020) - [j12]Maia Angelova, Gleb Beliakov, Sergiy Shelyag, Ye Zhu:
Density estimates on the unit simplex and calculation of the mode of a sample. Int. J. Intell. Syst. 35(5): 850-868 (2020) - [j11]Yushu Zhang, Jin Jiang, Yong Xiang, Ye Zhu, Liangtian Wan, Xiyuan Xie:
Cloud-assisted privacy-conscious large-scale Markowitz portfolio. Inf. Sci. 527: 548-559 (2020) - [j10]Jian-Zhang Wu, Rui-Jie Xi, Ye Zhu:
Correlative decision preference information consistency check and comprehensive dominance representation method. J. Intell. Fuzzy Syst. 38(2): 2009-2019 (2020) - 2019
- [j9]Maia Angelova, Gleb Beliakov, Ye Zhu:
Density-based clustering using approximate natural neighbours. Appl. Soft Comput. 85 (2019) - [j8]Kai Ming Ting, Ye Zhu, Mark J. Carman, Yue Zhu, Takashi Washio, Zhi-Hua Zhou:
Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms. Mach. Learn. 108(2): 331-376 (2019) - [j7]Ming Li, Di Xiao, Ye Zhu, Yushu Zhang, Lin Sun:
Commutative fragile zero-watermarking and encryption for image integrity protection. Multim. Tools Appl. 78(16): 22727-22742 (2019) - 2018
- [j6]Maia Angelova, Jeremy Ellman, Helen Gibson, Paul Oman, Sutharshan Rajasegarar, Ye Zhu:
User Activity Pattern Analysis in Telecare Data. IEEE Access 6: 33306-33317 (2018) - [j5]Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, Ye Zhu, Jonathan R. Wells:
Isolation-based anomaly detection using nearest-neighbor ensembles. Comput. Intell. 34(4): 968-998 (2018) - [j4]Bo Chen, Kai Ming Ting, Takashi Washio, Ye Zhu:
Local contrast as an effective means to robust clustering against varying densities. Mach. Learn. 107(8-10): 1621-1645 (2018) - [j3]Ye Zhu, Kai Ming Ting, Mark J. Carman:
Grouping points by shared subspaces for effective subspace clustering. Pattern Recognit. 83: 230-244 (2018) - 2016
- [j2]Ye Zhu, Kai Ming Ting:
Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems. Mach. Learn. 105(2): 301-304 (2016) - [j1]Ye Zhu, Kai Ming Ting, Mark James Carman:
Density-ratio based clustering for discovering clusters with varying densities. Pattern Recognit. 60: 983-997 (2016)
Conference and Workshop Papers
- 2024
- [c18]Lei Gong, Hang Zhang, Zongyou Liu, Kai Ming Ting, Yang Cao, Ye Zhu:
Local Subsequence-Based Distribution for Time Series Clustering. PAKDD (1) 2024: 259-270 - 2023
- [c17]Zijing Wang, Ye Zhu, Kai Ming Ting:
Distribution-Based Trajectory Clustering. ICDM 2023: 1379-1384 - [c16]Hang Zhang, Kaifeng Zhang, Kai Ming Ting, Ye Zhu:
Towards a Persistence Diagram that is Robust to Noise and Varied Densities. ICML 2023: 41952-41972 - [c15]Chen Li, Yang Cao, Ye Zhu, Jinli Zhang, Annisa, Debo Cheng, Huidong Tang, Shuai Jiang, Kenta Maruyama, Yasuhiko Morimoto:
An Enhanced Distributed Algorithm for Area Skyline Computation Based on Apache Spark. KSEM (4) 2023: 35-43 - [c14]Yuhang Liu, Yi Zhang, Yang Cao, Ye Zhu, Nayyar Zaidi, Chathu Ranaweera, Gang Li, Qingyi Zhu:
Kernel-Based Feature Extraction for Time Series Clustering. KSEM (1) 2023: 276-283 - [c13]Baojie Zhang, Yang Cao, Ye Zhu, Sutharshan Rajasegarar, Gang Liu, Hong Xian Li, Maia Angelova, Gang Li:
An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering. PAKDD (1) 2023: 197-209 - 2022
- [c12]Mingxi Wang, Ye Zhu, Gang Li, Gang Liu, Bo Yang:
Image Anomaly Detection With Semantic- Enhanced Augmentation and Distributional Kernel. HPCC/DSS/SmartCity/DependSys 2022: 163-170 - [c11]Ye Zhu, Kai Ming Ting:
Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel (Extended Abstract). IJCAI 2022: 5792-5796 - [c10]Xin Han, Ye Zhu, Kai Ming Ting, De-Chuan Zhan, Gang Li:
Streaming Hierarchical Clustering Based on Point-Set Kernel. KDD 2022: 525-533 - 2021
- [c9]Lu Zhou, Ye Zhu, Yong Xiang:
A Comprehensive Feature Importance Evaluation for DDoS Attacks Detection. ADMA 2021: 353-367 - [c8]Jillian Tallboys, Ye Zhu, Sutharshan Rajasegarar:
Identification of Stock Market Manipulation with Deep Learning. ADMA 2021: 408-420 - [c7]Xichen Tang, Jinlong Wang, Ye Zhu, Robin Doss, Xin Han:
Systematic evaluation of abnormal detection methods on gas well sensor data. ISCC 2021: 1-6 - 2019
- [c6]Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent C. S. Lee:
Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering. AAAI 2019: 4755-4762 - 2018
- [c5]Yuan Jin, Mark J. Carman, Ye Zhu, Wray L. Buntine:
Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing. ACML 2018: 192-207 - [c4]Yuan Jin, Lan Du, Ye Zhu, Mark J. Carman:
Leveraging Label Category Relationships in Multi-class Crowdsourcing. PAKDD (2) 2018: 128-140 - [c3]Ye Zhu, Kai Ming Ting, Maia Angelova:
A Distance Scaling Method to Improve Density-Based Clustering. PAKDD (3) 2018: 389-400 - 2016
- [c2]Kai Ming Ting, Ye Zhu, Mark James Carman, Yue Zhu, Zhi-Hua Zhou:
Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. KDD 2016: 1205-1214 - 2014
- [c1]Hua Lou, Ye Zhu:
Bivariate probability-based anomaly detection. BESC 2014: 81-86
Informal and Other Publications
- 2024
- [i13]Chen Li, Ye Zhu, Yang Cao, Jinli Zhang, Annisa, Debo Cheng, Yasuhiko Morimoto:
Mining Area Skyline Objects from Map-based Big Data using Apache Spark Framework. CoRR abs/2404.03254 (2024) - 2023
- [i12]Chen Li, Yang Cao, Ye Zhu, Debo Cheng, Chengyuan Li, Yasuhiko Morimoto:
Ripple Knowledge Graph Convolutional Networks For Recommendation Systems. CoRR abs/2305.01147 (2023) - [i11]Zijing Wang, Ye Zhu, Kai Ming Ting:
Distribution-Based Trajectory Clustering. CoRR abs/2310.05123 (2023) - 2022
- [i10]Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Gang Li:
Detecting Change Intervals with Isolation Distributional Kernel. CoRR abs/2212.14630 (2022) - 2021
- [i9]Kai Ming Ting, Takashi Washio, Ye Zhu, Yang Xu:
Breaking the curse of dimensionality with Isolation Kernel. CoRR abs/2109.14198 (2021) - 2020
- [i8]Kai Ming Ting, Jonathan R. Wells, Ye Zhu:
Clustering based on Point-Set Kernel. CoRR abs/2002.05815 (2020) - [i7]Xin Han, Ye Zhu, Kai Ming Ting, Gang Li:
The Impact of Isolation Kernel on Agglomerative Hierarchical Clustering Algorithms. CoRR abs/2010.05473 (2020) - 2019
- [i6]Ye Zhu, Kai Ming Ting:
Improving Stochastic Neighbour Embedding fundamentally with a well-defined data-dependent kernel. CoRR abs/1906.09744 (2019) - [i5]Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent C. S. Lee:
Nearest-Neighbour-Induced Isolation Similarity and its Impact on Density-Based Clustering. CoRR abs/1907.00378 (2019) - 2018
- [i4]Yuan Jin, Mark James Carman, Ye Zhu, Wray L. Buntine:
Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing. CoRR abs/1802.04009 (2018) - [i3]Ye Zhu, Kai Ming Ting, Mark J. Carman, Maia Angelova:
CDF Transform-Shift: An effective way to deal with inhomogeneous density datasets. CoRR abs/1810.02897 (2018) - [i2]Ye Zhu, Kai Ming Ting, Yuan Jin, Maia Angelova:
Hierarchical clustering that takes advantage of both density-peak and density-connectivity. CoRR abs/1810.03393 (2018) - [i1]Yuan Jin, Mark J. Carman, Ye Zhu, Yong Xiang:
A Technical Survey on Statistical Modelling and Design Methods for Crowdsourcing Quality Control. CoRR abs/1812.02736 (2018)
Coauthor Index
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last updated on 2024-05-27 23:40 CEST by the dblp team
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