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ZHIQIANG XU
ZHIQIANG XU
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
Verified email at mbzuai.ac.ae
Title
Cited by
Cited by
Year
A model-based approach to attributed graph clustering
Z Xu, Y Ke, Y Wang, H Cheng, J Cheng
Proceedings of the 2012 ACM SIGMOD international conference on management of …, 2012
4172012
GBAGC: A general Bayesian framework for attributed graph clustering
Z Xu, Y Ke, Y Wang, H Cheng, J Cheng
ACM Transactions on Knowledge Discovery from Data (TKDD) 9 (1), 1-43, 2014
862014
Agile and accurate CTR prediction model training for massive-scale online advertising systems
Z Xu, D Li, W Zhao, X Shen, T Huang, X Li, P Li
Proceedings of the 2021 international conference on management of data, 2404 …, 2021
412021
Efficient attribute-constrained co-located community search
J Luo, X Cao, X Xie, Q Qu, Z Xu, CS Jensen
2020 IEEE 36th International Conference on Data Engineering (ICDE), 1201-1212, 2020
242020
Effective and efficient spectral clustering on text and link data
Z Xu, Y Ke
Proceedings of the 25th ACM International on Conference on Information and …, 2016
232016
Towards better generalization of adaptive gradient methods
Y Zhou, B Karimi, J Yu, Z Xu, P Li
Advances in Neural Information Processing Systems 33, 810-821, 2020
192020
Convergence analysis of gradient descent for eigenvector computation
Z Xu, X Cao, X Gao
International Joint Conferences on Artificial Intelligence, 2018
162018
Towards practical alternating least-squares for CCA
Z Xu, P Li
Advances in Neural Information Processing Systems 32, 2019
152019
Group representation theory for knowledge graph embedding
C Cai, Y Cai, M Sun, Z Xu
arXiv preprint arXiv:1909.05100, 2019
132019
On truly block eigensolvers via riemannian optimization
Z Xu, X Gao
International Conference on Artificial Intelligence and Statistics, 168-177, 2018
112018
Gradient descent meets shift-and-invert preconditioning for eigenvector computation
Z Xu
Advances in Neural Information Processing Systems 31, 2018
102018
A practical Riemannian algorithm for computing dominant generalized Eigenspace
Z Xu, P Li
Conference on Uncertainty in Artificial Intelligence, 819-828, 2020
92020
Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering
Z Xu, J Cheng, X Xiao, R Fujimaki, Y Muraoka
Knowledge and Information Systems 53, 239-268, 2017
92017
Stochastic variance reduced Riemannian eigensolver
Z Xu, Y Ke
arXiv preprint arXiv:1605.08233, 2016
72016
Unsupervised video domain adaptation: A disentanglement perspective
P Wei, L Kong, X Qu, X Yin, Z Xu, J Jiang, Z Ma
arXiv preprint arXiv:2208.07365, 2022
52022
Faster noisy power method
Z Xu, P Li
International Conference on Algorithmic Learning Theory, 1138-1164, 2022
42022
A Comprehensively Tight Analysis of Gradient Descent for PCA
Z Xu, P Li
Advances in Neural Information Processing Systems 34, 21935-21946, 2021
42021
On the riemannian search for eigenvector computation
Z Xu, P Li
The Journal of Machine Learning Research 22 (1), 11301-11346, 2021
42021
Matrix eigen-decomposition via doubly stochastic riemannian optimization
Z Xu, P Zhao, J Cao, X Li
International conference on machine learning, 1660-1669, 2016
42016
Accelerate MaxBRkNN search by kNN estimation
X Chen, X Cao, Z Xu, Y Zhang, S Shang, W Zhang
2019 IEEE 35th International Conference on Data Engineering (ICDE), 1730-1733, 2019
32019
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