Graph regularized sparse coding for image representation M Zheng, J Bu, C Chen, C Wang, L Zhang, G Qiu, D Cai IEEE transactions on image processing 20 (5), 1327-1336, 2010 | 686 | 2010 |
Music recommendation by unified hypergraph: combining social media information and music content J Bu, S Tan, C Chen, C Wang, H Wu, L Zhang, X He Proceedings of the 18th ACM international conference on Multimedia, 391-400, 2010 | 392 | 2010 |
Expert finding for question answering via graph regularized matrix completion Z Zhao, L Zhang, X He, W Ng IEEE Transactions on Knowledge and Data Engineering 27 (4), 993-1004, 2014 | 197 | 2014 |
Adaptive online learning in dynamic environments L Zhang, S Lu, ZH Zhou Advances in neural information processing systems 31, 2018 | 188 | 2018 |
Linear convergence with condition number independent access of full gradients L Zhang, M Mahdavi, R Jin Advances in Neural Information Processing Systems 26, 2013 | 177 | 2013 |
Active learning based on locally linear reconstruction L Zhang, C Chen, J Bu, D Cai, X He, TS Huang IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (10), 2026 …, 2011 | 161 | 2011 |
Robust non-negative matrix factorization L Zhang, Z Chen, M Zheng, X He Frontiers of Electrical and Electronic Engineering in China 6, 192-200, 2011 | 156 | 2011 |
Tracking slowly moving clairvoyant: Optimal dynamic regret of online learning with true and noisy gradient T Yang, L Zhang, R Jin, J Yi International Conference on Machine Learning, 449-457, 2016 | 144 | 2016 |
Document summarization based on data reconstruction Z He, C Chen, J Bu, C Wang, L Zhang, D Cai, X He Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 620-626, 2012 | 144 | 2012 |
Improved dynamic regret for non-degenerate functions L Zhang, T Yang, J Yi, R Jin, ZH Zhou Advances in Neural Information Processing Systems 30, 2017 | 131 | 2017 |
Dynamic regret of strongly adaptive methods L Zhang, T Yang, ZH Zhou International conference on machine learning, 5882-5891, 2018 | 124 | 2018 |
Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD) Q Qian, R Jin, J Yi, L Zhang, S Zhu Machine Learning 99, 353-372, 2015 | 115 | 2015 |
Dynamic regret of convex and smooth functions P Zhao, YJ Zhang, L Zhang, ZH Zhou Advances in Neural Information Processing Systems 33, 12510-12520, 2020 | 97 | 2020 |
Graph regularized feature selection with data reconstruction Z Zhao, X He, D Cai, L Zhang, W Ng, Y Zhuang IEEE Transactions on Knowledge and Data Engineering 28 (3), 689-700, 2015 | 93 | 2015 |
Efficient algorithms for robust one-bit compressive sensing L Zhang, J Yi, R Jin international conference on machine learning, 820-828, 2014 | 92 | 2014 |
A simple approach for non-stationary linear bandits P Zhao, L Zhang, Y Jiang, ZH Zhou International Conference on Artificial Intelligence and Statistics, 746-755, 2020 | 91 | 2020 |
Learning with feature evolvable streams BJ Hou, L Zhang, ZH Zhou Advances in Neural Information Processing Systems 30, 2017 | 91 | 2017 |
Recovering the optimal solution by dual random projection L Zhang, M Mahdavi, R Jin, T Yang, S Zhu Conference on Learning Theory, 135-157, 2013 | 87 | 2013 |
Multi-view concept learning for data representation Z Guan, L Zhang, J Peng, J Fan IEEE Transactions on Knowledge and Data Engineering 27 (11), 3016-3028, 2015 | 83 | 2015 |
VR-SGD: A simple stochastic variance reduction method for machine learning F Shang, K Zhou, H Liu, J Cheng, IW Tsang, L Zhang, D Tao, L Jiao IEEE Transactions on Knowledge and Data Engineering 32 (1), 188-202, 2018 | 75 | 2018 |