The following publications are possibly variants of this publication:
- Adversarial robustness of deep neural networks: A survey from a formal verification perspectiveMeng, Mark Huasong, Bai, Guangdong, Teo, Sin Gee, Hou, Zhe, Xiao, Yan, Lin, Yun, Dong, Jin Song. IEEE Transactions on Dependable and Secure Computing, , 2022.
- Learning Distributed Representations and Deep Embedded Clustering of TextsShuang Wang, Amin Beheshti, Yufei Wang 0003, Jianchao Lu, Quan Z. Sheng, Stephen Elbourn, Hamid Alinejad-Rokny. algorithms, 16(3):158, March 2023. [doi]
- Improving spectral clustering with deep embedding, cluster estimation and metric learningLiang Duan, Shuai Ma 0001, Charu Aggarwal 0001, Saket Sathe 0001. kais, 63(3):675-694, 2021. [doi]
- Improving Spectral Clustering with Deep Embedding and Cluster EstimationLiang Duan, Charu C. Aggarwal, Shuai Ma 0001, Saket Sathe. icdm 2019: 170-179 [doi]
- Learning Multimodal Taxonomy via Variational Deep Graph Embedding and ClusteringHuaiwen Zhang, Quan Fang, Shengsheng Qian, Changsheng Xu. mm 2018: 681-689 [doi]
- A Deep Clustering via Automatic Feature Embedded Learning for Human Activity RecognitionTing Wang, Wing W. Y. Ng, Jinde Li, Qiuxia Wu, Shuai Zhang 0001, Chris D. Nugent, Colin Shewell. tcsv, 32(1):210-223, 2022. [doi]
- Program restructuring through clustering techniquesXia Xu, Chung-Horng Lung, Zaman, M., Srinivasan, A.. In Source Code Analysis and Manipulation, 2004. Fourth IEEE International Workshop on. 2004: [doi]
- Clustering based Contrastive Learning for Improving Face RepresentationsVivek Sharma 0001, Makarand Tapaswi, M. Saquib Sarfraz, Rainer Stiefelhagen. fgr 2020: 109-116 [doi]