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ORCIDLijun Zhang 0005
张利军
Person information
- unicode name: 张利军
- affiliation: Nanjing University, National Key Laboratory for Novel Software Technology, China
- affiliation (2012 - 2014): Michigan State University, Department of Computer Science and Engineering, East Lansing, MI, USA
- affiliation (PhD 2012): Zhejiang University, College of Computer Science, China
Other persons with the same name
- Lijun Zhang (aka: Li-jun Zhang, Li-Jun Zhang, Li Jun Zhang) — disambiguation page
- Lijun Zhang 0001
![[0000-0002-3692-2088]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-3692-2088")
— Chinese Academy of Sciences, School of Software, Beijing, China (and 2 more) - Lijun Zhang 0002 — Tsinghua University, Department of Electronic Engineering, Beijing, China
- Lijun Zhang 0003 — Northwestern Polytechnical University, School of Computer Science and Technology, Xi'an, China
- Lijun Zhang 0004 — Northwestern Polytechnical University, Center of Intelligent Acoustics and Immersive Communications, Xi'an, China (and 1 more)
- Lijun Zhang 0006 — University of Science & Technology of China, Department of Modern Physics, Hefei, China
- Lijun Zhang 0007 — University of Science and Technology Beijing, China
- Lijun Zhang 0008 — Institute of Clinical Pharmacology, Central South University, Changsha, China
- Lijun Zhang 0009 — University of Louisville, CECS Department, KY, USA
- Lijun Zhang 0010 — Hebei Univerity of Engineering, Handan, China
- Lijun Zhang 0011 — China Meteorol. Adm. (CMA), Beijing
- Lijun Zhang 0012 — Soochow University, Department of Engineering, Suzhou, China
- Lijun Zhang 0013 — Graduate University of Chinese Academy of Science, State Key Lab. of Information Security, China
- Lijun Zhang 0014 — University of Pretoria, Department of Electrical, Electronic and Computer Engineering, South Africa (and 1 more)
- Lijun Zhang 0016 — Chinese Academy of Sciences, Shanghai Advanced Research Institute, China (and 1 more)
- Lijun Zhang 0017 — Jilin University, College of Materials Science and Engineering, Changchun, China
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Journal Articles
- 2022
[j31]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Strongly adaptive online learning over partial intervals. Sci. China Inf. Sci. 65(10) (2022)- [j30]Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang:
Projection-free Distributed Online Learning with Sublinear Communication Complexity. J. Mach. Learn. Res. 23: 172:1-172:53 (2022) - [j29]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online strongly convex optimization with unknown delays. Mach. Learn. 111(3): 871-893 (2022) - [j28]Yuanyu Wan, Lijun Zhang:
Efficient Adaptive Online Learning via Frequent Directions. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6910-6923 (2022) - [j27]Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou:
Prediction With Unpredictable Feature Evolution. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5706-5715 (2022) - 2021
- [j26]Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou:
Bandit Convex Optimization in Non-stationary Environments. J. Mach. Learn. Res. 22: 125:1-125:45 (2021) - [j25]Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou:
Learning With Feature Evolvable Streams. IEEE Trans. Knowl. Data Eng. 33(6): 2602-2615 (2021) - [j24]Haipeng Dai, Ke Sun, Alex X. Liu, Lijun Zhang, Jiaqi Zheng, Guihai Chen:
Charging Task Scheduling for Directional Wireless Charger Networks. IEEE Trans. Mob. Comput. 20(11): 3163-3180 (2021) - 2020
- [j23]Yuanyu Wan, Lijun Zhang:
Accelerating adaptive online learning by matrix approximation. Int. J. Data Sci. Anal. 9(4): 389-400 (2020) - [j22]Tianbao Yang, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin:
High-dimensional model recovery from random sketched data by exploring intrinsic sparsity. Mach. Learn. 109(5): 899-938 (2020) - [j21]Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32(1): 188-202 (2020) - 2019
- [j20]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion. J. Mach. Learn. Res. 20: 97:1-97:22 (2019) - [j19]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou:
A simple homotopy proximal mapping algorithm for compressive sensing. Mach. Learn. 108(6): 1019-1056 (2019) - 2017
- [j18]Sen Yang, Lijun Zhang:
Non-redundant multiple clustering by nonnegative matrix factorization. Mach. Learn. 106(5): 695-712 (2017) - [j17]Weizhong Zhang, Lijun Zhang, Zhongming Jin, Rong Jin, Deng Cai, Xuelong Li, Ronghua Liang, Xiaofei He:
Sparse Learning with Stochastic Composite Optimization. IEEE Trans. Pattern Anal. Mach. Intell. 39(6): 1223-1236 (2017) - 2016
- [j16]Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang:
Online kernel learning with nearly constant support vectors. Neurocomputing 179: 26-36 (2016) - [j15]Xiaofei He, Chiyuan Zhang, Lijun Zhang, Xuelong Li:
A-Optimal Projection for Image Representation. IEEE Trans. Pattern Anal. Mach. Intell. 38(5): 1009-1015 (2016) - [j14]Zhou Zhao, Xiaofei He, Deng Cai, Lijun Zhang, Wilfred Ng, Yueting Zhuang:
Graph Regularized Feature Selection with Data Reconstruction. IEEE Trans. Knowl. Data Eng. 28(3): 689-700 (2016) - 2015
- [j13]Zhanying He, Chun Chen, Jiajun Bu, Can Wang, Lijun Zhang, Deng Cai, Xiaofei He:
Unsupervised document summarization from data reconstruction perspective. Neurocomputing 157: 356-366 (2015) - [j12]Ping Li, Jiajun Bu, Lijun Zhang, Chun Chen:
Graph-based local concept coordinate factorization. Knowl. Inf. Syst. 43(1): 103-126 (2015) - [j11]Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu:
Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). Mach. Learn. 99(3): 353-372 (2015) - [j10]Zhou Zhao, Lijun Zhang, Xiaofei He, Wilfred Ng:
Expert Finding for Question Answering via Graph Regularized Matrix Completion. IEEE Trans. Knowl. Data Eng. 27(4): 993-1004 (2015) - [j9]Ziyu Guan, Lijun Zhang, Jinye Peng, Jianping Fan:
Multi-View Concept Learning for Data Representation. IEEE Trans. Knowl. Data Eng. 27(11): 3016-3028 (2015) - 2014
- [j8]Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu:
Random Projections for Classification: A Recovery Approach. IEEE Trans. Inf. Theory 60(11): 7300-7316 (2014) - 2012
- [j7]Hao Wu, Jiajun Bu, Chun Chen, Jianke Zhu, Lijun Zhang, Haifeng Liu, Can Wang, Deng Cai:
Locally discriminative topic modeling. Pattern Recognit. 45(1): 617-625 (2012) - [j6]Lijun Zhang, Chun Chen, Jiajun Bu, Xiaofei He:
A Unified Feature and Instance Selection Framework Using Optimum Experimental Design. IEEE Trans. Image Process. 21(5): 2379-2388 (2012) - [j5]Lijun Zhang, Chun Chen, Jiajun Bu, Zhengguang Chen, Deng Cai, Jiawei Han:
Locally Discriminative Coclustering. IEEE Trans. Knowl. Data Eng. 24(6): 1025-1035 (2012) - 2011
- [j4]Lijun Zhang, Chun Chen, Jiajun Bu, Deng Cai, Xiaofei He, Thomas S. Huang:
Active Learning Based on Locally Linear Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 33(10): 2026-2038 (2011) - [j3]Miao Zheng, Jiajun Bu, Chun Chen, Can Wang, Lijun Zhang, Guang Qiu, Deng Cai:
Graph Regularized Sparse Coding for Image Representation. IEEE Trans. Image Process. 20(5): 1327-1336 (2011) - 2010
- [j2]Chun Chen, Lijun Zhang, Jiajun Bu, Can Wang, Wei Chen:
Constrained Laplacian Eigenmap for dimensionality reduction. Neurocomputing 73(4-6): 951-958 (2010) - [j1]Wei Chen, Chun Chen, Lijun Zhang, Can Wang, Jiajun Bu:
Online detection of bursty events and their evolution in news streams. J. Zhejiang Univ. Sci. C 11(5): 340-355 (2010)
Conference and Workshop Papers
- 2024
- [c107]Wenhao Yang, Yingchun Jian, Yibo Wang, Shiyin Lu, Lei Shen, Bing Wang, Haihong Tang, Lijun Zhang:
Not All Embeddings are Created Equal: Towards Robust Cross-domain Recommendation via Contrastive Learning. WWW 2024: 3195-3206 - 2023
- [c106]Yibo Wang, Yuanyu Wan, Shimao Zhang, Lijun Zhang:
Distributed Projection-Free Online Learning for Smooth and Convex Losses. AAAI 2023: 10226-10234 - [c105]Yuanyu Wan, Lijun Zhang, Mingli Song:
Improved Dynamic Regret for Online Frank-Wolfe. COLT 2023: 3304-3327 - [c104]Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. ICML 2023: 5002-5035 - [c103]Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang:
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. ICML 2023: 13550-13583 - [c102]Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang:
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. ICML 2023: 28389-28421 - [c101]Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. NeurIPS 2023 - [c100]Lijun Zhang, Peng Zhao, Zhen-Hua Zhuang, Tianbao Yang, Zhi-Hua Zhou:
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. NeurIPS 2023 - [c99]Yutian Gou, Jinfeng Yi, Lijun Zhang:
Stochastic Graphical Bandits with Heavy-Tailed Rewards. UAI 2023: 734-744 - 2022
- [c98]Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang:
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. AISTATS 2022: 3753-3771 - [c97]Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang:
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. ICML 2022: 10195-10216 - [c96]Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang:
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. ICML 2022: 18122-18152 - [c95]Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang:
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. ICML 2022: 25760-25782 - [c94]Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang:
A Simple yet Universal Strategy for Online Convex Optimization. ICML 2022: 26605-26623 - [c93]Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou:
Efficient Methods for Non-stationary Online Learning. NeurIPS 2022 - [c92]Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang:
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. NeurIPS 2022 - [c91]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online Frank-Wolfe with Arbitrary Delays. NeurIPS 2022 - [c90]Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang:
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. NeurIPS 2022 - [c89]Yingchun Jian, Jinfeng Yi, Lijun Zhang:
Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. PAKDD (1) 2022: 276-289 - [c88]Shiyin Lu, Yu-Hang Zhou, Jing-Cheng Shi, Wenya Zhu, Qingtao Yu, Qing-Guo Chen, Qing Da, Lijun Zhang:
Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization. WSDM 2022: 618-627 - 2021
- [c87]Shiyin Lu, Guanghui Wang, Lijun Zhang:
Stochastic Graphical Bandits with Adversarial Corruptions. AAAI 2021: 8749-8757 - [c86]Shiyin Lu, Yao Hu, Lijun Zhang:
Stochastic Bandits with Graph Feedback in Non-Stationary Environments. AAAI 2021: 8758-8766 - [c85]Yuanyu Wan, Lijun Zhang:
Approximate Multiplication of Sparse Matrices with Limited Space. AAAI 2021: 10058-10066 - [c84]Yuanyu Wan, Bo Xue, Lijun Zhang:
Projection-free Online Learning in Dynamic Environments. AAAI 2021: 10067-10075 - [c83]Yuanyu Wan, Lijun Zhang:
Projection-free Online Learning over Strongly Convex Sets. AAAI 2021: 10076-10084 - [c82]Zi-Hao Qiu, Ying-Chun Jian, Qing-Guo Chen, Lijun Zhang:
Learning to Augment Imbalanced Data for Re-ranking Models. CIKM 2021: 1478-1487 - [c81]Yimu Wang, Bo Xue, Quan Cheng, Yuhui Chen, Lijun Zhang:
Deep Unified Cross-Modality Hashing by Pairwise Data Alignment. IJCAI 2021: 1129-1135 - [c80]Peng Zhao, Lijun Zhang:
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. L4DC 2021: 48-59 - [c79]Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang:
Revisiting Smoothed Online Learning. NeurIPS 2021: 13599-13612 - [c78]Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou:
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. NeurIPS 2021: 24968-24980 - [c77]Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang:
Online Convex Optimization with Continuous Switching Constraint. NeurIPS 2021: 28636-28647 - 2020
- [c76]Guanghui Wang, Shiyin Lu, Yao Hu, Lijun Zhang:
Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization. AAAI 2020: 6162-6169 - [c75]Lijun Zhang, Shiyin Lu, Tianbao Yang:
Minimizing Dynamic Regret and Adaptive Regret Simultaneously. AISTATS 2020: 309-319 - [c74]Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou:
A Simple Approach for Non-stationary Linear Bandits. AISTATS 2020: 746-755 - [c73]Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou:
Bandit Convex Optimization in Non-stationary Environments. AISTATS 2020: 1508-1518 - [c72]Pengcheng Li, Runze Li, Qing Da, Anxiang Zeng, Lijun Zhang:
Improving Multi-Scenario Learning to Rank in E-commerce by Exploiting Task Relationships in the Label Space. CIKM 2020: 2605-2612 - [c71]Guanghui Wang, Shiyin Lu, Quan Cheng, Weiwei Tu, Lijun Zhang:
SAdam: A Variant of Adam for Strongly Convex Functions. ICLR 2020 - [c70]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity. ICML 2020: 9818-9828 - [c69]Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang:
Stochastic Optimization for Non-convex Inf-Projection Problems. ICML 2020: 10660-10669 - [c68]Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang:
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. IJCAI 2020: 2936-2942 - [c67]Lijun Zhang:
Online Learning in Changing Environments. IJCAI 2020: 5178-5182 - [c66]Yimu Wang, Shiyin Lu, Lijun Zhang:
Searching Privately by Imperceptible Lying: A Novel Private Hashing Method with Differential Privacy. ACM Multimedia 2020: 2700-2709 - [c65]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Dynamic Regret of Convex and Smooth Functions. NeurIPS 2020 - [c64]Yimu Wang, Xiu-Shen Wei, Bo Xue, Lijun Zhang:
Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search. PRCV (2) 2020: 432-444 - [c63]Yimu Wang, Ren-Jie Song, Xiu-Shen Wei, Lijun Zhang:
An Adversarial Domain Adaptation Network For Cross-Domain Fine-Grained Recognition. WACV 2020: 1217-1225 - 2019
- [c62]Lijun Zhang, Zhi-Hua Zhou:
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate. COLT 2019: 3160-3179 - [c61]Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang:
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards. ICML 2019: 4154-4163 - [c60]Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou:
Adaptive Regret of Convex and Smooth Functions. ICML 2019: 7414-7423 - [c59]Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang:
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. IJCAI 2019: 2909-2915 - [c58]Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang:
Multi-Objective Generalized Linear Bandits. IJCAI 2019: 3080-3086 - [c57]Guanghui Wang, Shiyin Lu, Lijun Zhang:
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. UAI 2019: 659-668 - 2018
- [c56]Tianbao Yang, Zhe Li, Lijun Zhang:
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer. AISTATS 2018: 445-453 - [c55]Pengcheng Li, Jinfeng Yi, Lijun Zhang:
Query-Efficient Black-Box Attack by Active Learning. ICDM 2018: 1200-1205 - [c54]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Dynamic Regret of Strongly Adaptive Methods. ICML 2018: 5877-5886 - [c53]Haipeng Dai, Ke Sun, Alex X. Liu, Lijun Zhang, Jiaqi Zheng, Guihai Chen:
Charging Task Scheduling for Directional Wireless Charger Networks. ICPP 2018: 10:1-10:10 - [c52]Yuanyu Wan, Nan Wei, Lijun Zhang:
Efficient Adaptive Online Learning via Frequent Directions. IJCAI 2018: 2748-2754 - [c51]Guanghui Wang, Dakuan Zhao, Lijun Zhang:
Minimizing Adaptive Regret with One Gradient per Iteration. IJCAI 2018: 2762-2768 - [c50]Lijun Zhang, Zhi-Hua Zhou:
\ell_1-regression with Heavy-tailed Distributions. NeurIPS 2018: 1084-1094 - [c49]Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou:
Adaptive Online Learning in Dynamic Environments. NeurIPS 2018: 1330-1340 - [c48]Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang:
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. NeurIPS 2018: 4683-4694 - [c47]Yuanyu Wan, Lijun Zhang:
Accelerating Adaptive Online Learning by Matrix Approximation. PAKDD (2) 2018: 405-417 - 2017
- [c46]Jie Zhang, Lijun Zhang:
Efficient Stochastic Optimization for Low-Rank Distance Metric Learning. AAAI 2017: 933-940 - [c45]Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin:
A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis. AAAI 2017: 2224-2230 - [c44]Yi Xu, Haiqin Yang, Lijun Zhang, Tianbao Yang:
Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee. AAAI 2017: 2796-2802 - [c43]Lijun Zhang, Tianbao Yang, Rong Jin:
Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds. COLT 2017: 1954-1979 - [c42]Tianbao Yang, Qihang Lin, Lijun Zhang:
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates. ICML 2017: 3901-3910 - [c41]Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou:
Storage Fit Learning with Unlabeled Data. IJCAI 2017: 1844-1850 - [c40]Yichi Xiao, Zhe Li, Tianbao Yang, Lijun Zhang:
SVD-free Convex-Concave Approaches for Nuclear Norm Regularization. IJCAI 2017: 3126-3132 - [c39]Xinyu Yan, Lijun Zhang, Wu-Jun Li:
Semi-Supervised Deep Hashing with a Bipartite Graph. IJCAI 2017: 3238-3244 - [c38]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Improved Dynamic Regret for Non-degenerate Functions. NIPS 2017: 732-741 - [c37]Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou:
Learning with Feature Evolvable Streams. NIPS 2017: 1417-1427 - [c36]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Scalable Demand-Aware Recommendation. NIPS 2017: 2412-2421 - 2016
- [c35]Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin:
Fast and Accurate Refined Nyström-Based Kernel SVM. AAAI 2016: 1830-1836 - [c34]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Stochastic Optimization for Kernel PCA. AAAI 2016: 2315-2322 - [c33]Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He:
Accelerated Sparse Linear Regression via Random Projection. AAAI 2016: 2337-2343 - [c32]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach. ALT 2016: 83-97 - [c31]Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-Hua Zhou:
Online Stochastic Linear Optimization under One-bit Feedback. ICML 2016: 392-401 - [c30]Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi:
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. ICML 2016: 449-457 - [c29]Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang:
Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. UAI 2016 - 2015
- [c28]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Online Bandit Learning for a Special Class of Non-Convex Losses. AAAI 2015: 3158-3164 - [c27]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
A Simple Homotopy Algorithm for Compressive Sensing. AISTATS 2015 - [c26]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. COLT 2015: 1305-1320 - [c25]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu:
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection. ICML 2015: 135-143 - [c24]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu:
Theory of Dual-sparse Regularized Randomized Reduction. ICML 2015: 305-314 - [c23]Jinfeng Yi, Lijun Zhang, Tianbao Yang, Wei Liu, Jun Wang:
An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints. KDD 2015: 1405-1414 - 2014
- [c22]Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He:
Sparse Learning for Stochastic Composite Optimization. AAAI 2014: 893-900 - [c21]Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil K. Jain:
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data. ICML 2014: 658-666 - [c20]Lijun Zhang, Jinfeng Yi, Rong Jin:
Efficient Algorithms for Robust One-bit Compressive Sensing. ICML 2014: 820-828 - 2013
- [c19]Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu:
Recovering the Optimal Solution by Dual Random Projection. COLT 2013: 135-157 - [c18]Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He:
Online Kernel Learning with a Near Optimal Sparsity Bound. ICML (3) 2013: 621-629 - [c17]Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He:
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions. ICML (3) 2013: 1121-1129 - [c16]Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil K. Jain:
Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. ICML (3) 2013: 1400-1408 - [c15]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Mixed Optimization for Smooth Functions. NIPS 2013: 674-682 - [c14]Lijun Zhang, Mehrdad Mahdavi, Rong Jin:
Linear Convergence with Condition Number Independent Access of Full Gradients. NIPS 2013: 980-988 - 2012
- [c13]Zhanying He, Chun Chen, Jiajun Bu, Can Wang, Lijun Zhang, Deng Cai, Xiaofei He:
Document Summarization Based on Data Reconstruction. AAAI 2012: 620-626 - [c12]Lijun Zhang, Rong Jin, Chun Chen, Jiajun Bu, Xiaofei He:
Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression. AAAI 2012: 1219-1225 - [c11]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou:
Multiple Kernel Learning from Noisy Labels by Stochastic Programming. ICML 2012 - 2011
- [c10]Ruifeng Huang, Jianbin Zheng, Lijun Zhang, Zhaoyong Zhang, Hao Wu, Yue Yu:
Word line boost and read SA PMOS compensation (SAPC) for ROM in 55nm CMOS. ASICON 2011: 307-310 - 2010
- [c9]Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, Lijun Zhang, Cheng Zhang:
G-Optimal Design with Laplacian Regularization. AAAI 2010: 413-418 - [c8]Hao Wu, Jiajun Bu, Chun Chen, Can Wang, Guang Qiu, Lijun Zhang, Jianfeng Shen:
Modeling Dynamic Multi-Topic Discussions in Online Forums. AAAI 2010: 1455-1460 - [c7]Jiajia Zheng, Wei Chen, Lijun Zhang, Jiajun Bu, Chun Chen:
A Metric for Measuring Members' Contribution to Information Propagation in Social Network Sites. APWeb 2010: 392-394 - [c6]Lijun Zhang, Chun Chen, Jiajun Bu, Zhengguang Chen, Shulong Tan, Xiaofei He:
Discriminative codeword selection for image representation. ACM Multimedia 2010: 173-182 - [c5]Jiajun Bu, Shulong Tan, Chun Chen, Can Wang, Hao Wu, Lijun Zhang, Xiaofei He:
Music recommendation by unified hypergraph: combining social media information and music content. ACM Multimedia 2010: 391-400 - [c4]Wei Chen, Can Wang, Chun Chen, Lijun Zhang, Jiajun Bu:
Topic Decomposition and Summarization. PAKDD (1) 2010: 440-448 - 2009
- [c3]Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng Cai, Xiaofei He:
Convex experimental design using manifold structure for image retrieval. ACM Multimedia 2009: 45-54 - 2008
- [c2]Wei Chen, Lijun Zhang, Can Wang, Chun Chen, Jiajun Bu:
Pervasive Web News Recommendation for Visually Impaired People. Web Intelligence/IAT Workshops 2008: 119-122 - 2007
- [c1]Kangmiao Liu, Wei Chen, Jiajun Bu, Chun Chen, Lijun Zhang:
User Modeling for Recommendation in Blogspace. Web Intelligence/IAT Workshops 2007: 79-82
Informal and Other Publications
- 2024
- [i76]Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang:
Improved Regret for Bandit Convex Optimization with Delayed Feedback. CoRR abs/2402.09152 (2024) - [i75]Yuanyu Wan, Tong Wei, Mingli Song, Lijun Zhang:
Nearly Optimal Regret for Decentralized Online Convex Optimization. CoRR abs/2402.09173 (2024) - [i74]Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang:
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. CoRR abs/2404.04575 (2024) - [i73]Sijia Chen, Yibo Wang, Yi-Feng Wu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang:
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees. CoRR abs/2406.07115 (2024) - 2023
- [i72]Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. CoRR abs/2302.04552 (2023) - [i71]Yuanyu Wan, Lijun Zhang, Mingli Song:
Improved Dynamic Regret for Online Frank-Wolfe. CoRR abs/2302.05620 (2023) - [i70]Lijun Zhang, Peng Zhao, Tianbao Yang, Zhi-Hua Zhou:
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. CoRR abs/2302.09267 (2023) - [i69]Yibo Wang, Wenhao Yang, Wei Jiang, Shiyin Lu, Bing Wang, Haihong Tang, Yuanyu Wan, Lijun Zhang:
Non-stationary Projection-free Online Learning with Dynamic and Adaptive Regret Guarantees. CoRR abs/2305.11726 (2023) - [i68]Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang:
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. CoRR abs/2305.11965 (2023) - [i67]Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang:
Non-stationary Online Convex Optimization with Arbitrary Delays. CoRR abs/2305.12131 (2023) - [i66]Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang:
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. CoRR abs/2305.18730 (2023) - [i65]Lijun Zhang, Wei-Wei Tu:
Efficient Stochastic Approximation of Minimax Excess Risk Optimization. CoRR abs/2306.00026 (2023) - [i64]Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang:
Learning Unnormalized Statistical Models via Compositional Optimization. CoRR abs/2306.07485 (2023) - [i63]Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou:
Efficient Methods for Non-stationary Online Learning. CoRR abs/2309.08911 (2023) - [i62]Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. CoRR abs/2310.18701 (2023) - 2022
- [i61]Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang:
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. CoRR abs/2202.07530 (2022) - [i60]Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang:
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. CoRR abs/2202.12183 (2022) - [i59]Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang:
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. CoRR abs/2202.12387 (2022) - [i58]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online Frank-Wolfe with Unknown Delays. CoRR abs/2204.04964 (2022) - [i57]Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang:
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. CoRR abs/2205.00741 (2022) - [i56]Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang:
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. CoRR abs/2207.08540 (2022) - 2021
- [i55]Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang:
Revisiting Smoothed Online Learning. CoRR abs/2102.06933 (2021) - [i54]Peng Zhao, Lijun Zhang:
Non-stationary Linear Bandits Revisited. CoRR abs/2103.05324 (2021) - [i53]Yuanyu Wan, Guanghui Wang, Lijun Zhang:
Projection-free Distributed Online Learning with Strongly Convex Losses. CoRR abs/2103.11102 (2021) - [i52]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online Strongly Convex Optimization with Unknown Delays. CoRR abs/2103.11354 (2021) - [i51]Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang:
Online Convex Optimization with Continuous Switching Constraint. CoRR abs/2103.11370 (2021) - [i50]Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang:
A Simple yet Universal Strategy for Online Convex Optimization. CoRR abs/2105.03681 (2021) - [i49]Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang:
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. CoRR abs/2107.01173 (2021) - [i48]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. CoRR abs/2112.14368 (2021) - 2020
- [i47]Lijun Zhang, Shiyin Lu, Tianbao Yang:
Minimizing Dynamic Regret and Adaptive Regret Simultaneously. CoRR abs/2002.02085 (2020) - [i46]Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang:
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. CoRR abs/2004.13465 (2020) - [i45]Peng Zhao, Lijun Zhang:
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. CoRR abs/2006.05876 (2020) - [i44]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Dynamic Regret of Convex and Smooth Functions. CoRR abs/2007.03479 (2020) - [i43]Yuanyu Wan, Lijun Zhang:
Approximate Multiplication of Sparse Matrices with Limited Space. CoRR abs/2009.03527 (2020) - [i42]Yuanyu Wan, Lijun Zhang:
Projection-free Online Learning over Strongly Convex Sets. CoRR abs/2010.08177 (2020) - 2019
- [i41]Lijun Zhang, Zhi-Hua Zhou:
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the O(1/T) Convergence Rate. CoRR abs/1901.09344 (2019) - [i40]Yan Yan, Yi Xu, Qihang Lin, Lijun Zhang, Tianbao Yang:
Stochastic Primal-Dual Algorithms with Faster Convergence than O(1/√T) for Problems without Bilinear Structure. CoRR abs/1904.10112 (2019) - [i39]Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou:
Adaptive Regret of Convex and Smooth Functions. CoRR abs/1904.11681 (2019) - [i38]Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou:
Prediction with Unpredictable Feature Evolution. CoRR abs/1904.12171 (2019) - [i37]Guanghui Wang, Shiyin Lu, Weiwei Tu, Lijun Zhang:
SAdam: A Variant of Adam for Strongly Convex Functions. CoRR abs/1905.02957 (2019) - [i36]Guanghui Wang, Shiyin Lu, Lijun Zhang:
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. CoRR abs/1905.05917 (2019) - [i35]Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang:
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. CoRR abs/1905.11713 (2019) - [i34]Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang:
Multi-Objective Generalized Linear Bandits. CoRR abs/1905.12879 (2019) - [i33]Lijun Zhang, Guanghui Wang, Weiwei Tu, Zhi-Hua Zhou:
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. CoRR abs/1906.10851 (2019) - [i32]Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou:
Bandit Convex Optimization in Non-stationary Environments. CoRR abs/1907.12340 (2019) - [i31]Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang:
Stochastic Optimization for Non-convex Inf-Projection Problems. CoRR abs/1908.09941 (2019) - [i30]Shiyin Lu, Lijun Zhang:
More Adaptive Algorithms for Tracking the Best Expert. CoRR abs/1909.02187 (2019) - 2018
- [i29]Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR abs/1802.09932 (2018) - [i28]Lijun Zhang, Zhi-Hua Zhou:
𝓁1-regression with Heavy-tailed Distributions. CoRR abs/1805.00616 (2018) - [i27]Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang:
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. CoRR abs/1805.04577 (2018) - [i26]Yuanyu Wan, Jinfeng Yi, Lijun Zhang:
Matrix Completion from Non-Uniformly Sampled Entries. CoRR abs/1806.10308 (2018) - [i25]Pengcheng Li, Jinfeng Yi, Lijun Zhang:
Query-Efficient Black-Box Attack by Active Learning. CoRR abs/1809.04913 (2018) - [i24]Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou:
Adaptive Online Learning in Dynamic Environments. CoRR abs/1810.10815 (2018) - 2017
- [i23]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Strongly Adaptive Regret Implies Optimally Dynamic Regret. CoRR abs/1701.07570 (2017) - [i22]Lijun Zhang, Tianbao Yang, Rong Jin:
Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n2)-type of Risk Bounds. CoRR abs/1702.02030 (2017) - [i21]Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li:
Positive-Unlabeled Demand-Aware Recommendation. CoRR abs/1702.06347 (2017) - [i20]Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou:
Learning with Feature Evolvable Streams. CoRR abs/1706.05259 (2017) - [i19]Tianbao Yang, Zhe Li, Lijun Zhang:
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer. CoRR abs/1709.02909 (2017) - 2016
- [i18]Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi:
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. CoRR abs/1605.04638 (2016) - [i17]Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou:
Improved dynamic regret for non-degeneracy functions. CoRR abs/1608.03933 (2016) - [i16]Yi Xu, Haiqin Yang, Lijun Zhang, Tianbao Yang:
Efficient Non-oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee. CoRR abs/1612.01663 (2016) - 2015
- [i15]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu:
Theory of Dual-sparse Regularized Randomized Reduction. CoRR abs/1504.03991 (2015) - [i14]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Analysis of Nuclear Norm Regularization for Full-rank Matrix Completion. CoRR abs/1504.06817 (2015) - [i13]Tianbao Yang, Lijun Zhang, Qihang Lin, Rong Jin:
Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees. CoRR abs/1507.05185 (2015) - [i12]Qi Qian, Rong Jin, Lijun Zhang, Shenghuo Zhu:
Towards Making High Dimensional Distance Metric Learning Practical. CoRR abs/1509.04355 (2015) - [i11]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Online Stochastic Linear Optimization under One-bit Feedback. CoRR abs/1509.07728 (2015) - [i10]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Stochastic Proximal Gradient Descent for Nuclear Norm Regularization. CoRR abs/1511.01664 (2015) - [i9]Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach. CoRR abs/1511.03766 (2015) - 2014
- [i8]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Binary Excess Risk for Smooth Convex Surrogates. CoRR abs/1402.1792 (2014) - [i7]Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu:
A Simple Homotopy Proximal Mapping for Compressive Sensing. CoRR abs/1412.1205 (2014) - 2013
- [i6]Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He:
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions. CoRR abs/1304.0740 (2013) - [i5]Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu:
Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD). CoRR abs/1304.1192 (2013) - [i4]Tianbao Yang, Lijun Zhang:
Efficient Stochastic Gradient Descent for Strongly Convex Optimization. CoRR abs/1304.5504 (2013) - [i3]Lijun Zhang, Mehrdad Mahdavi, Rong Jin:
Improving the Minimax Rate of Active Learning. CoRR abs/1311.4803 (2013) - 2012
- [i2]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou:
Multiple Kernel Learning from Noisy Labels by Stochastic Programming. CoRR abs/1206.4629 (2012) - [i1]Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang:
Recovering Optimal Solution by Dual Random Projection. CoRR abs/1211.3046 (2012)
Coauthor Index
[j22] [j20] [j19] [j17] [j16] [j11] [j8] [c54] [c48] [c45] [c43] [c38] [c35] [c34] [c33] [c32] [c31] [c30] [c28] [c27] [c26] [c25] [c24] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c12] [c11] [i27] [i23] [i22] [i18] [i17] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i3] [i2] [i1]
Wei-Wei Tu
aka: Weiwei Tu
aka: Weiwei Tu
[j22] [j20] [j19] [j8] [c103] [c102] [c100] [c98] [c97] [c96] [c95] [c94] [c92] [c90] [c79] [c77] [c75] [c69] [c56] [c54] [c48] [c45] [c44] [c43] [c42] [c40] [c38] [c35] [c34] [c32] [c31] [c30] [c29] [c28] [c27] [c25] [c24] [c23] [c19] [c17] [c11] [i74] [i70] [i68] [i66] [i64] [i61] [i60] [i59] [i57] [i56] [i55] [i51] [i50] [i49] [i47] [i40] [i31] [i27] [i23] [i22] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i11] [i10] [i9] [i7] [i6] [i4] [i2] [i1]
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