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Lizhong Ding (丁立中)
Lizhong Ding (丁立中)
Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, UAE
Verified email at inceptioniai.org
Title
Cited by
Cited by
Year
Deep learning in bioinformatics: Introduction, application, and perspective in the big data era
Y Li, C Huang, L Ding, Z Li, Y Pan, X Gao
Methods 166, 4-21, 2019
3582019
Multi-class learning: From theory to algorithm
J Li, Y Liu, R Yin, H Zhang, L Ding, W Wang
Advances in Neural Information Processing Systems 31, 2018
522018
Fast cross-validation for kernel-based algorithms
Y Liu, S Liao, S Jiang, L Ding, H Lin, W Wang
IEEE transactions on pattern analysis and machine intelligence 42 (5), 1083-1096, 2019
432019
On the decision boundary of deep neural networks
Y Li, L Ding, X Gao
arXiv preprint arXiv:1808.05385, 2018
432018
Sail: Self-augmented graph contrastive learning
L Yu, S Pei, L Ding, J Zhou, L Li, C Zhang, X Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8927-8935, 2022
382022
Supportnet: solving catastrophic forgetting in class incremental learning with support data
Y Li, Z Li, L Ding, Y Pan, C Huang, Y Hu, W Chen, X Gao
arXiv preprint arXiv:1806.02942, 2018
372018
Approximate model selection for large scale LSSVM
L Ding, S Liao
Asian Conference on Machine Learning, 165-180, 2011
332011
An approximate approach to automatic kernel selection
L Ding, S Liao
IEEE Transactions on Cybernetics 47 (3), 554-565, 2016
242016
Dynamically visual disambiguation of keyword-based image search
Y Yao, Z Sun, F Shen, L Liu, L Wang, F Zhu, L Ding, G Wu, L Shao
arXiv preprint arXiv:1905.10955, 2019
212019
Approximate kernel selection via matrix approximation
L Ding, S Liao, Y Liu, L Liu, F Zhu, Y Yao, L Shao, X Gao
IEEE Transactions on Neural Networks and Learning Systems 31 (11), 4881-4891, 2020
202020
Fast Cross-Validation.
Y Liu, H Lin, L Ding, W Wang, S Liao
IJCAI, 2497-2503, 2018
202018
Randomized kernel selection with spectra of multilevel circulant matrices
L Ding, S Liao, Y Liu, P Yang, X Gao
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
152018
Systematic selection of chemical fingerprint features improves the Gibbs energy prediction of biochemical reactions
M Alazmi, H Kuwahara, O Soufan, L Ding, X Gao
Bioinformatics 35 (15), 2634-2643, 2019
122019
Linear kernel tests via empirical likelihood for high-dimensional data
L Ding, Z Liu, Y Li, S Liao, Y Liu, P Yang, G Yu, L Shao, X Gao
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3454-3461, 2019
112019
Model selection with the covering number of the ball of RKHS
L Ding, S Liao
Proceedings of the 23rd ACM International Conference on Conference on …, 2014
102014
Nyström approximate model selection for LSSVM
L Ding, S Liao
Advances in Knowledge Discovery and Data Mining: 16th Pacific-Asia …, 2012
102012
Approximate consistency: Towards foundations of approximate kernel selection
L Ding, S Liao
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014
92014
KMA-𝛼: a kernel matrix approximation algorithm for support vector machines
L Ding, S Liao
Computer Research and Development 49 (4), 746-753, 2012
92012
Learning with uncertain kernel matrix set
L Jia, SZ Liao, LZ Ding
Journal of Computer Science and Technology 25 (4), 709-727, 2010
92010
Predictive Nyström method for kernel methods
J Wu, L Ding, S Liao
Neurocomputing 234, 116-125, 2017
82017
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Articles 1–20