Lijun Zhang's Publications

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Preprints

  1. Strongly Adaptive Regret Implies Optimally Dynamic Regret [arXiv]
    L. Zhang, T. Yang, R. Jin, and Z.-H. Zhou

  2. Analysis of Nuclear Norm Regularization for Full-rank Matrix Completion [arXiv]
    L. Zhang, T. Yang, R. Jin, and Z.-H. Zhou

Conference (*student author)

  1. Improved Dynamic Regret for Non-degenerate Functions [arXiv]
    L. Zhang, T. Yang, J. Yi, R. Jin, and Z.-H. Zhou
    In Advances in Neural Information Processing Systems 30 (NIPS 2017), to appear, 2017.

  2. Learning with Feature Evolvable Streams [arXiv]
    B.-J. Hou, L. Zhang, and Z.-H. Zhou
    In Advances in Neural Information Processing Systems 30 (NIPS 2017), to appear, 2017.

  3. Scalable Demand-Aware Recommendation [arXiv]
    J. Yi, C.-J. Hsieh, K. Varshney, L. Zhang, and Y. Li
    In Advances in Neural Information Processing Systems 30 (NIPS 2017), to appear, 2017.

  4. Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n^2)-type of Risk Bounds [PDF, Bibtex]
    L. Zhang, T. Yang, and R. Jin
    In Proceedings of the 30th Annual Conference on Learning Theory (COLT 2017), pages 1954 - 1979, 2017.

  5. A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates [PDF, Bibtex, Full Version]
    T. Yang, Q. Lin, and L. Zhang
    In Proceedings of the 34th International Conference on Machine Learning (ICML 2017), pages 3901 - 3910, 2017.

  6. Semi-Supervised Deep Hashing with a Bipartite Graph [PDF, Bibtex]
    X. Yan*, L. Zhang, and W.-J. Li
    In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pages 3238 - 3244, 2017.

  7. Storage Fit Learning with Unlabeled Data [PDF, Bibtex]
    B.-J. Hou, L. Zhang, and Z.-H. Zhou
    In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pages 1844 - 1850, 2017.

  8. SVD-free Convex-Concave Approaches for Nuclear Norm Regularization [PDF, Supplementary, Bibtex]
    Y. Xiao*, Z. Li, T. Yang, and L. Zhang
    In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pages 3126 - 3132, 2017.

  9. Efficient Stochastic Optimization for Low-Rank Distance Metric Learning [PDF, Supplementary, Bibtex]
    J. Zhang*, and L. Zhang
    In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017), pages 933 - 939, 2017.

  10. A Two-stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis [PDF, Bibtex]
    Z. Li, T. Yang, L. Zhang, and R. Jin
    In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017), pages 2224 - 2230, 2017.

  11. Efficient Non-oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee [PDF, Bibtex]
    Y. Xu, H. Yang, L. Zhang, and T. Yang
    In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017), pages 2796 - 2802, 2017.

  12. Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach [PDF, Supplementary, Bibtex, Full Version]
    L. Zhang, T. Yang, R. Jin, and Z.-H. Zhou
    In Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT 2016), pages 83 - 97, 2016.

  13. Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections [PDF, Supplementary, Bibtex]
    J. Chen, T. Yang, Q. Lin, L. Zhang, and Y. Chang
    In Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), pages 122 - 131, 2016.

  14. Online Stochastic Linear Optimization under One-bit Feedback [PDF, Supplementary, Bibtex]
    L. Zhang, T. Yang, R. Jin, Y. Xiao, and Z.-H. Zhou
    In Proceedings of the 33rd International Conference on Machine Learning (ICML 2016), 2016.

  15. Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient [PDF, Supplementary, Bibtex]
    T. Yang, L. Zhang, R. Jin, and J. Yi
    In Proceedings of the 33rd International Conference on Machine Learning (ICML 2016), 2016.

  16. Stochastic Optimization for Kernel PCA [PDF, Supplementary, Bibtex]
    L. Zhang, T. Yang, J. Yi, R. Jin, and Z.-H. Zhou
    In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016), pages 2316 - 2322, 2016.

  17. Accelerated Sparse Linear Regression via Random Projection [PDF, Bibtex]
    W. Zhang, L. Zhang, R. Jin, D. Cai, and X. He
    In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016), pages 2337 - 2343, 2016.

  18. Fast and Accurate Refined Nystrom Based Kernel SVM [PDF, Bibtex]
    Z. Li, T. Yang, L. Zhang, and R. Jin
    In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016), pages 1830 - 1836, 2016.

  19. An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints [PDF, Bibtex]
    J. Yi, L. Zhang, T. Yang, W. Liu, and J. Wang
    In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015), pages 1405 - 1414, 2015.

  20. Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization [PDF, Errata, Bibtex]
    M. Mahdavi, L. Zhang, and R. Jin
    In Proceedings of the 28th Conference on Learning Theory (COLT 2015), 2015.

  21. An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection [PDF, Bibtex]
    T. Yang, L. Zhang, R. Jin, and S. Zhu
    In Proceedings of the 32nd International Conference on Machine Learning (ICML 2015), 2015.

  22. Theory of Dual-Sparse Regularized Randomized Reduction [PDF, Bibtex]
    T. Yang, L. Zhang, R. Jin, and S. Zhu
    In Proceedings of the 32nd International Conference on Machine Learning (ICML 2015), 2015.

  23. A Simple Homotopy Algorithm for Compressive Sensing [PDF, Supplementary, Bibtex]
    L. Zhang, T. Yang, R. Jin, and Z.-H. Zhou
    In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS 2015), pages 1116 - 1124, 2015.

  24. Online Bandit Learning for a Special Class of Non-convex Losses [PDF, Supplementary, Bibtex]
    L. Zhang, T. Yang, R. Jin, and Z.-H. Zhou
    In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015), pages 3158 - 3164, 2015.

  25. Efficient Algorithms for Robust One-bit Compressive Sensing [PDF, Supplementary, Bibtex]
    L. Zhang, J. Yi, and R. Jin
    In Proceedings of the 31st International Conference on Machine Learning (ICML 2014), 2014.

  26. A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data [PDF, Supplementary, Bibtex]
    J. Yi, L. Zhang, J. Wang, R. Jin, and A. Jain
    In Proceedings of the 31st International Conference on Machine Learning (ICML 2014), 2014.

  27. Sparse Learning for Stochastic Composite Optimization [PDF, Bibtex]
    W. Zhang, L. Zhang, Y. Hu, R. Jin, D. Cai, and X. He
    In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), pages 893 - 899, 2014.

  28. Linear Convergence with Condition Number Independent Access of Full Gradients [PDF, Bibtex]
    L. Zhang, M. Mahdavi, and R. Jin
    In Advances in Neural Information Processing Systems 26 (NIPS 2013), pages 980 - 988, 2013.

  29. Mixed Optimization for Smooth Functions [PDF, Supplementary, Bibtex]
    M. Mahdavi, L. Zhang, and R. Jin
    In Advances in Neural Information Processing Systems 26 (NIPS 2013), pages 674 - 682, 2013.

  30. Recovering the Optimal Solution by Dual Random Projection [PDF, Bibtex, Journal Version]
    L. Zhang, M. Mahdavi, R. Jin, T. Yang, and S. Zhu
    In Proceedings of the 26th Conference on Learning Theory (COLT 2013), pages 135 - 157, 2013.

  31. Online Kernel Learning with a Near Optimal Sparsity Bound [PDF, Supplementary, Bibtex]
    L. Zhang, J. Yi, R. Jin, M. Lin, and X. He
    In Proceedings of the 30th International Conference on Machine Learning (ICML 2013), pages 621 - 629, 2013.

  32. O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions [PDF, Supplementary, Bibtex]
    L. Zhang, T. Yang, R. Jin, and X. He
    In Proceedings of the 30th International Conference on Machine Learning (ICML 2013), pages 1121 - 1129, 2013.

  33. Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion [PDF, Bibtex]
    J. Yi, L. Zhang, R. Jin, Q. Qian, and A. Jain
    In Proceedings of the 30th International Conference on Machine Learning (ICML 2013), pages 1400 - 1408, 2013.

  34. Multiple Kernel Learning from Noisy Labels by Stochastic Programming [PDF, Bibtex]
    T. Yang, M. Mahdavi, R. Jin, L. Zhang, and Y. Zhou
    In Proceedings of the 29th International Conference on Machine Learning (ICML 2012), pages 233 - 240, 2012.

  35. Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression [PDF, Bibtex]
    L. Zhang, R. Jin, C. Chen, J. Bu, and X. He
    In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI 2012), pages 1219 - 1225, 2012.

  36. Document Summarization Based on Data Reconstruction [PDF, Bibtex] (AAAI-12 Outstanding Paper Awards)
    Z. He, C. Chen, J. Bu, C. Wang, L. Zhang, D. Cai, and X. He
    In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI 2012), pages 620 - 626, 2012.

  37. Discriminative Codeword Selection for Image Representation [PDF, Bibtex]
    L. Zhang, C. Chen, J. Bu, Z. Chen, S. Tan, and X. He
    In Proceedings of the 18th ACM International Conference on Multimedia (ACM Multimedia 2010), pages 173 - 182, 2010.

  38. Music Recommendation by Unified Hypergraph: Combining Social Media Information and Music Content [PDF, Bibtex]
    J. Bu, S. Tan, C. Chen, C. Wang, H. Wu, L. Zhang, and X. He
    In Proceedings of the 18th ACM International Conference on Multimedia (ACM Multimedia 2010), pages 391 - 400, 2010.

  39. G-Optimal Design with Laplacian Regularization [PDF, Bibtex]
    C. Chen, Z. Chen, J. Bu, C. Wang, L. Zhang, and C. Zhang
    In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI 2010), pages 413 - 418, 2010.

  40. Modeling Dynamic Multi-Topic Discussions in Online Forums [PDF, Bibtex]
    H. Wu, J. Bu, C. Chen, C. Wang, G. Qiu, L. Zhang, and J. Shen
    In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI 2010), pages 1455 - 1460, 2010.

  41. Convex Experimental Design Using Manifold Structure for Image Retrieval [PDF, Bibtex]
    L. Zhang, C. Chen, W. Chen, J. Bu, D. Cai, and X. He
    In Proceedings of the 17th ACM International Conference on Multimedia (ACM Multimedia 2009), pages 45 - 53, 2009.

Journal (*student author)

  1. Sparse Learning with Stochastic Composite Optimization [PDF, Bibtex]
    W. Zhang, L. Zhang, Z. Jin, R. Jin, D. Cai, X. Li, R. Liang, and X. He
    IEEE Transactions on Pattern Analysis & Machine Intelligence (TPAMI), 39(6): 1223 - 1236, 2017.

  2. Non-redundant Multiple Clustering by Nonnegative Matrix Factorization [PDF, Bibtex]
    S. Yang*, and L. Zhang
    Machine Learning, 106(5): 695 - 712, 2017.

  3. A-Optimal Projection for Image Representation [PDF, Appendix, Bibtex]
    X. He, C. Zhang, L. Zhang, and X. Li
    IEEE Transactions on Pattern Analysis & Machine Intelligence (TPAMI), 38(5): 1009 - 1015, 2016.

  4. Graph Regularized Feature Selection with Data Reconstruction [PDF, Bibtex]
    Z. Zhao, X. He, D. Cai, L. Zhang, W. Ng, and Y. Zhuang
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(3): 689 - 700, 2016.

  5. Online Kernel Learning with Nearly Constant Support Vectors [PDF, Bibtex]
    M. Lin, L. Zhang, R. Jin, S. Weng, and C. Zhang
    Neurocomputing, 179: 26 - 36, 2016.

  6. Multi-View Concept Learning for Data Representation [PDF, Bibtex]
    Z. Guan, L. Zhang, J. Peng, and J. Fan
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(11): 3016 - 3028, 2015.

  7. Expert Finding for Question Answering via Graph Regularized Matrix Completion [PDF, Bibtex]
    Z. Zhao, L. Zhang, X. He, and W. Ng
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(4): 993 - 1004, 2015.

  8. Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD) [PDF, Bibtex]
    Q. Qian, R. Jin, J. Yi, L. Zhang, and S. Zhu
    Machine Learning, 99(3): 353 - 372, 2015.

  9. Graph-Based Local Concept Coordinate Factorization [PDF, Bibtex]
    P. Li, J. Bu, L. Zhang, and C. Chen
    Knowledge and Information Systems (KAIS), 43(1): 103 - 126, 2015.

  10. Unsupervised Document Summarization from Data Reconstruction Perspective [PDF, Bibtex]
    Z. He, C. Chen, J. Bu, C. Wang, L. Zhang, D. Cai, and X. He
    Neurocomputing, 157: 356 - 366, 2015.

  11. Random Projections for Classification: A Recovery Approach [PDF, Bibtex]
    L. Zhang, M. Mahdavi, R. Jin, T. Yang, and S. Zhu
    IEEE Transactions on Information Theory (TIT), 60(11): 7300 - 7316, 2014.

  12. Locally Regressive Projections [PDF, Bibtex]
    L. Zhang
    International Journal of Software and Informatics (IJSI), 7(3): 435 - 451, 2013.

  13. Locally Discriminative Coclustering [PDF, Bibtex]
    L. Zhang, C. Chen, J. Bu, Z. Chen, D. Cai, and J. Han
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 24(6): 1025 - 1035, 2012.

  14. A Unified Feature and Instance Selection Framework Using Optimum Experimental Design [PDF, Bibtex]
    L. Zhang, C. Chen, J. Bu, and X. He
    IEEE Transactions on Image Processing (TIP), 21(5): 2379 - 2388, 2012.

  15. Locally Discriminative Topic Modeling [PDF, Bibtex]
    H. Wu, J. Bu, C. Chen, J. Zhu, L. Zhang, H. Liu, C. Wang, and D. Cai
    Pattern Recognition, 45(1): 617 - 625, 2012.

  16. Active Learning Based on Locally Linear Reconstruction [PDF, Appendix, Bibtex]
    L. Zhang, C. Chen, J. Bu, D. Cai, X. He, and T. Huang
    IEEE Transactions on Pattern Analysis & Machine Intelligence (TPAMI), 33(10): 2026 - 2038, 2011.

  17. Graph Regularized Sparse Coding for Image Representation [PDF, Bibtex]
    M. Zheng, J. Bu, C. Chen, C. Wang, L. Zhang, G. Qiu, and D. Cai
    IEEE Transactions on Image Processing (TIP), 20(5): 1327 - 1336, 2011.

  18. Robust Non-negative Matrix Factorization [PDF, Bibtex]
    L. Zhang, Z. Chen, M. Zheng, and X. He
    Frontiers of Electrical and Electronic Engineering in China, 6(2): 192 - 200, 2011.

  19. Constrained Laplacian Eigenmap for Dimensionality Reduction [PDF, Bibtex]
    C. Chen, L. Zhang, J. Bu, C. Wang, and W. Chen
    Neurocomputing, 73(4-6): 951 - 958, 2010.