Ye Zhu

According to our database, Ye Zhu authored at least 61 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Automation and Orchestration of Zero Trust Architecture: Potential Solutions and Challenges.

Yang Cao, Shiva Raj Pokhrel, Ye Zhu, Robin Doss, Gang Li

Mach. Intell. Res., April, 2024

Mitigating the Impact of a False Message Through Sequential Release of Clarifying Messages.

Kaifan Huang, Xiaofan Yang, Lu-Xing Yang, Ye Zhu, Gang Li

IEEE Trans. Netw. Sci. Eng., 2024

Detecting Change Intervals with Isolation Distributional Kernel.

Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Luxing Yang, Gang Li

J. Artif. Intell. Res., 2024

2023

Social tie-driven coupling propagation of user awareness and information in Device-to-Device communications.

Chenquan Gan, Anqi Liu, Qingyi Zhu, Ye Zhu, Yong Xiang, Jun Liu

Comput. Networks, December, 2023

Anomaly detection of vectorized time series on aircraft battery data.

Moting Su, Wenjie Zhao, Ye Zhu, Donglan Zha, Yushu Zhang, Peng Xu

Expert Syst. Appl., October, 2023

The impact of isolation kernel on agglomerative hierarchical clustering algorithms.

Xin Han, Ye Zhu, Kai Ming Ting, Gang Li

Pattern Recognit., July, 2023

Kernel-based clustering via Isolation Distributional Kernel.

Ye Zhu, Kai Ming Ting

Inf. Syst., July, 2023

CFNet: Facial expression recognition via constraint fusion under multi-task joint learning network.

Junhao Xiao, Chenquan Gan, Qingyi Zhu, Ye Zhu, Gang Liu

Appl. Soft Comput., July, 2023

Point-Set Kernel Clustering.

Kai Ming Ting, Jonathan R. Wells, Ye Zhu

IEEE Trans. Knowl. Data Eng., May, 2023

Modelling host population support for combat adversaries.

Mathew Zuparic, Sergiy Shelyag, Maia Angelova, Ye Zhu, Alexander C. Kalloniatis

J. Oper. Res. Soc., March, 2023

Isolation Kernel Estimators.

Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang, Ye Zhu

Knowl. Inf. Syst., February, 2023

A novel feature-based framework enabling multi-type DDoS attacks detection.

Lu Zhou, Ye Zhu, Yong Xiang, Tianrui Zong

World Wide Web (WWW), January, 2023

Clustering-enhanced stock price prediction using deep learning.

Man Li, Ye Zhu, Yuxin Shen, Maia Angelova

World Wide Web (WWW), January, 2023

Ripple Knowledge Graph Convolutional Networks For Recommendation Systems.

Chen Li, Yang Cao, Ye Zhu, Debo Cheng, Chengyuan Li, Yasuhiko Morimoto

CoRR, 2023

An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering.

Baojie Zhang, Yang Cao, Ye Zhu, Sutharshan Rajasegarar, Gang Liu, Hong Xian Li, Maia Angelova, Gang Li

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Kernel-Based Feature Extraction for Time Series Clustering.

Yuhang Liu, Yi Zhang, Yang Cao, Ye Zhu, Nayyar Zaidi, Chathu Ranaweera, Gang Li, Qingyi Zhu

Proceedings of the Knowledge Science, Engineering and Management, 2023

An Enhanced Distributed Algorithm for Area Skyline Computation Based on Apache Spark.

Chen Li, Yang Cao, Ye Zhu, Jinli Zhang, Annisa, Debo Cheng, Huidong Tang, Shuai Jiang, Kenta Maruyama, Yasuhiko Morimoto

Proceedings of the Knowledge Science, Engineering and Management, 2023

Towards a Persistence Diagram that is Robust to Noise and Varied Densities.

Hang Zhang, Kaifeng Zhang, Kai Ming Ting, Ye Zhu

Proceedings of the International Conference on Machine Learning, 2023

Distribution-Based Trajectory Clustering.

Zijing Wang, Ye Zhu, Kai Ming Ting

Proceedings of the IEEE International Conference on Data Mining, 2023

2022

A New Distributional Treatment for Time Series and An Anomaly Detection Investigation.

Kai Ming Ting, Zongyou Liu, Hang Zhang, Ye Zhu

Proc. VLDB Endow., 2022

Noise-free thumbnail-preserving image encryption based on MSB prediction.

Ye Zhu, Ruoyu Zhao, Yushu Zhang, Xiangli Xiao, Rushi Lan, Yong Xiang

Inf. Sci., 2022

Hierarchical clustering that takes advantage of both density-peak and density-connectivity.

Ye Zhu, Kai Ming Ting, Yuan Jin, Maia Angelova

Inf. Syst., 2022

Weighted dynamic time warping for traffic flow clustering.

Man Li, Ye Zhu, Taige Zhao, Maia Angelova

Neurocomputing, 2022

A feature selection-based method for DDoS attack flow classification.

Lu Zhou, Ye Zhu, Tianrui Zong, Yong Xiang

Future Gener. Comput. Syst., 2022

Detecting Change Intervals with Isolation Distributional Kernel.

Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Gang Li

CoRR, 2022

Streaming Hierarchical Clustering Based on Point-Set Kernel.

Xin Han, Ye Zhu, Kai Ming Ting, De-Chuan Zhan, Gang Li

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel (Extended Abstract).

Ye Zhu, Kai Ming Ting

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Image Anomaly Detection With Semantic- Enhanced Augmentation and Distributional Kernel.

Mingxi Wang, Ye Zhu, Gang Li, Gang Liu, Bo Yang

Proceedings of the 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, 2022

2021

Anomaly detection of aircraft lead-acid battery.

Wenjie Zhao, Yushu Zhang, Ye Zhu, Peng Xu

Qual. Reliab. Eng. Int., 2021

CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities.

Ye Zhu, Kai Ming Ting, Mark J. Carman, Maia Angelova

Pattern Recognit., 2021

Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel.

Ye Zhu, Kai Ming Ting

J. Artif. Intell. Res., 2021

Breaking the curse of dimensionality with Isolation Kernel.

Kai Ming Ting, Takashi Washio, Ye Zhu, Yang Xu

CoRR, 2021

Adversarial decision strategies in multiple network phased oscillators: The Blue-Green-Red Kuramoto-Sakaguchi model.

Mathew Zuparic, Maia Angelova, Ye Zhu, Alexander C. Kalloniatis

Commun. Nonlinear Sci. Numer. Simul., 2021

Systematic evaluation of abnormal detection methods on gas well sensor data.

Xichen Tang, Jinlong Wang, Ye Zhu, Robin Doss, Xin Han

Proceedings of the IEEE Symposium on Computers and Communications, 2021

A Comprehensive Feature Importance Evaluation for DDoS Attacks Detection.

Lu Zhou, Ye Zhu, Yong Xiang

Proceedings of the Advanced Data Mining and Applications - 17th International Conference, 2021

Identification of Stock Market Manipulation with Deep Learning.

Jillian Tallboys, Ye Zhu, Sutharshan Rajasegarar

Proceedings of the Advanced Data Mining and Applications - 17th International Conference, 2021

2020

Correlative decision preference information consistency check and comprehensive dominance representation method.

Jian-Zhang Wu, Rui-Jie Xi, Ye Zhu

J. Intell. Fuzzy Syst., 2020

Cloud-assisted privacy-conscious large-scale Markowitz portfolio.

Yushu Zhang, Jin Jiang, Yong Xiang, Ye Zhu, Liangtian Wan, Xiyuan Xie

Inf. Sci., 2020

Density estimates on the unit simplex and calculation of the mode of a sample.

Maia Angelova, Gleb Beliakov, Sergiy Shelyag, Ye Zhu

Int. J. Intell. Syst., 2020

Clustering based on Point-Set Kernel.

Kai Ming Ting, Jonathan R. Wells, Ye Zhu

CoRR, 2020

A technical survey on statistical modelling and design methods for crowdsourcing quality control.

Yuan Jin, Mark J. Carman, Ye Zhu, Yong Xiang

Artif. Intell., 2020

Machine Learning Enabled Team Performance Analysis in the Dynamical Environment of Soccer.

Shitanshu Kusmakar, Sergiy Shelyag, Ye Zhu, Dan Dwyer, Paul B. Gastin, Maia Angelova

IEEE Access, 2020

Automated Method for Detecting Acute Insomnia Using Multi-Night Actigraphy Data.

Maia Angelova, Chandan K. Karmakar, Ye Zhu, Sean P. A. Drummond, Jason Ellis

IEEE Access, 2020

2019

Commutative fragile zero-watermarking and encryption for image integrity protection.

Ming Li, Di Xiao, Ye Zhu, Yushu Zhang, Lin Sun

Multim. Tools Appl., 2019

Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms.

Kai Ming Ting, Ye Zhu, Mark J. Carman, Yue Zhu, Takashi Washio, Zhi-Hua Zhou

Mach. Learn., 2019

Improving Stochastic Neighbour Embedding fundamentally with a well-defined data-dependent kernel.

Ye Zhu, Kai Ming Ting

CoRR, 2019

Density-based clustering using approximate natural neighbours.

Maia Angelova, Gleb Beliakov, Ye Zhu

Appl. Soft Comput., 2019

Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering.

Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent C. S. Lee

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Grouping points by shared subspaces for effective subspace clustering.

Ye Zhu, Kai Ming Ting, Mark J. Carman

Pattern Recognit., 2018

Local contrast as an effective means to robust clustering against varying densities.

Bo Chen, Kai Ming Ting, Takashi Washio, Ye Zhu

Mach. Learn., 2018

CDF Transform-Shift: An effective way to deal with inhomogeneous density datasets.

Ye Zhu, Kai Ming Ting, Mark J. Carman, Maia Angelova

CoRR, 2018

Isolation-based anomaly detection using nearest-neighbor ensembles.

Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, Ye Zhu, Jonathan R. Wells

Comput. Intell., 2018

User Activity Pattern Analysis in Telecare Data.

Maia Angelova, Jeremy Ellman, Helen Gibson, Paul Oman, Sutharshan Rajasegarar, Ye Zhu

IEEE Access, 2018

A Distance Scaling Method to Improve Density-Based Clustering.

Ye Zhu, Kai Ming Ting, Maia Angelova

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Leveraging Label Category Relationships in Multi-class Crowdsourcing.

Yuan Jin, Lan Du, Ye Zhu, Mark J. Carman

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing.

Yuan Jin, Mark J. Carman, Ye Zhu, Wray L. Buntine

Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017

Efficient Identification of Arbitrarily Shaped and Varied Density Clusters in High-dimensional Data.

Ye Zhu

PhD thesis, 2017

2016

Density-ratio based clustering for discovering clusters with varying densities.

Ye Zhu, Kai Ming Ting, Mark James Carman

Pattern Recognit., 2016

Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems.

Ye Zhu, Kai Ming Ting

Mach. Learn., 2016

Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure.

Kai Ming Ting, Ye Zhu, Mark James Carman, Yue Zhu, Zhi-Hua Zhou

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2014

Bivariate probability-based anomaly detection.

Hua Lou, Ye Zhu

Proceedings of the 2014 International Conference on Behavioral, 2014