Lijun Zhang

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 147

Top Venues

Publications

Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang
Improved Regret for Bandit Convex Optimization with Delayed Feedback. CoRR (2024)
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)
Yuanyu Wan, Tong Wei, Mingli Song, Lijun Zhang
Nearly Optimal Regret for Decentralized Online Convex Optimization. CoRR (2024)
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 (2024)
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 (2023)
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)
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)
Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. CoRR (2023)
Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. ICML (2023)
Lijun Zhang, Peng Zhao, Zhen-Hua Zhuang, Tianbao Yang, Zhi-Hua Zhou
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. NeurIPS (2023)
Yuanyu Wan, Lijun Zhang, Mingli Song
Improved Dynamic Regret for Online Frank-Wolfe. COLT (2023)
Lijun Zhang, Peng Zhao, Tianbao Yang, Zhi-Hua Zhou
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. CoRR (2023)
Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou
Efficient Methods for Non-stationary Online Learning. CoRR (2023)
Yuanyu Wan, Lijun Zhang, Mingli Song
Improved Dynamic Regret for Online Frank-Wolfe. CoRR (2023)
Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. NeurIPS (2023)
Yibo Wang, Yuanyu Wan, Shimao Zhang, Lijun Zhang
Distributed Projection-Free Online Learning for Smooth and Convex Losses. AAAI (2023)
Lijun Zhang, Wei-Wei Tu
Efficient Stochastic Approximation of Minimax Excess Risk Optimization. CoRR (2023)
Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. CoRR (2023)
Yutian Gou, Jinfeng Yi, Lijun Zhang
Stochastic Graphical Bandits with Heavy-Tailed Rewards. UAI (2023)
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 (2023)
Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang
Projection-free Distributed Online Learning with Sublinear Communication Complexity. J. Mach. Learn. Res. 23 (2022)
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)
Yuanyu Wan, Lijun Zhang
Efficient Adaptive Online Learning via Frequent Directions. IEEE Trans. Pattern Anal. Mach. Intell. 44 (10) (2022)
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 (2022)
Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. CoRR (2022)
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)
Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou
Efficient Methods for Non-stationary Online Learning. NeurIPS (2022)
Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. NeurIPS (2022)
Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
Prediction With Unpredictable Feature Evolution. IEEE Trans. Neural Networks Learn. Syst. 33 (10) (2022)
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Online Frank-Wolfe with Arbitrary Delays. NeurIPS (2022)
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)
Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. NeurIPS (2022)
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Online Frank-Wolfe with Unknown Delays. CoRR (2022)
Yingchun Jian, Jinfeng Yi, Lijun Zhang
Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. PAKDD (1) (2022)
Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. AISTATS (2022)
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Strongly adaptive online learning over partial intervals. Sci. China Inf. Sci. 65 (10) (2022)
Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
A Simple yet Universal Strategy for Online Convex Optimization. ICML (2022)
Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. ICML (2022)
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Online strongly convex optimization with unknown delays. Mach. Learn. 111 (3) (2022)
Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang
Revisiting Smoothed Online Learning. NeurIPS (2021)
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)
Yimu Wang, Bo Xue, Quan Cheng, Yuhui Chen, Lijun Zhang
Deep Unified Cross-Modality Hashing by Pairwise Data Alignment. IJCAI (2021)
Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang
Online Convex Optimization with Continuous Switching Constraint. NeurIPS (2021)
Shiyin Lu, Guanghui Wang, Lijun Zhang
Stochastic Graphical Bandits with Adversarial Corruptions. AAAI (2021)
Peng Zhao, Lijun Zhang
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. L4DC (2021)
Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang
Revisiting Smoothed Online Learning. CoRR (2021)
Yuanyu Wan, Bo Xue, Lijun Zhang
Projection-free Online Learning in Dynamic Environments. AAAI (2021)
Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang
Online Convex Optimization with Continuous Switching Constraint. CoRR (2021)
Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou
Bandit Convex Optimization in Non-stationary Environments. J. Mach. Learn. Res. 22 (2021)
Yuanyu Wan, Lijun Zhang
Projection-free Online Learning over Strongly Convex Sets. AAAI (2021)
Yuanyu Wan, Guanghui Wang, Lijun Zhang
Projection-free Distributed Online Learning with Strongly Convex Losses. CoRR (2021)
Yuanyu Wan, Lijun Zhang
Approximate Multiplication of Sparse Matrices with Limited Space. AAAI (2021)
Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. CoRR (2021)
Shiyin Lu, Yao Hu, Lijun Zhang
Stochastic Bandits with Graph Feedback in Non-Stationary Environments. AAAI (2021)
Peng Zhao, Lijun Zhang
Non-stationary Linear Bandits Revisited. CoRR (2021)
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) (2021)
Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
Learning With Feature Evolvable Streams. IEEE Trans. Knowl. Data Eng. 33 (6) (2021)
Zi-Hao Qiu, Ying-Chun Jian, Qing-Guo Chen, Lijun Zhang
Learning to Augment Imbalanced Data for Re-ranking Models. CIKM (2021)
Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
A Simple yet Universal Strategy for Online Convex Optimization. CoRR (2021)
Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. CoRR (2021)
Lijun Zhang, Shiyin Lu, Tianbao Yang
Minimizing Dynamic Regret and Adaptive Regret Simultaneously. AISTATS (2020)
Yuanyu Wan, Lijun Zhang
Approximate Multiplication of Sparse Matrices with Limited Space. CoRR (2020)
Yimu Wang, Shiyin Lu, Lijun Zhang
Searching Privately by Imperceptible Lying: A Novel Private Hashing Method with Differential Privacy. ACM Multimedia (2020)
Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou
A Simple Approach for Non-stationary Linear Bandits. AISTATS (2020)
Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
Dynamic Regret of Convex and Smooth Functions. CoRR (2020)
Guanghui Wang, Shiyin Lu, Quan Cheng, Weiwei Tu, Lijun Zhang
SAdam: A Variant of Adam for Strongly Convex Functions. ICLR (2020)
Guanghui Wang, Shiyin Lu, Yao Hu, Lijun Zhang
Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization. AAAI (2020)
Yuanyu Wan, Lijun Zhang
Accelerating adaptive online learning by matrix approximation. Int. J. Data Sci. Anal. 9 (4) (2020)
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity. ICML (2020)
Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou
Bandit Convex Optimization in Non-stationary Environments. AISTATS (2020)
Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
Dynamic Regret of Convex and Smooth Functions. NeurIPS (2020)
Peng Zhao, Lijun Zhang
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. CoRR (2020)
Yimu Wang, Xiu-Shen Wei, Bo Xue, Lijun Zhang
Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search. PRCV (2) (2020)
Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. IJCAI (2020)
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) (2020)
Lijun Zhang, Shiyin Lu, Tianbao Yang
Minimizing Dynamic Regret and Adaptive Regret Simultaneously. CoRR (2020)
Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. CoRR (2020)
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)
Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang
Stochastic Optimization for Non-convex Inf-Projection Problems. ICML (2020)
Yimu Wang, Ren-Jie Song, Xiu-Shen Wei, Lijun Zhang
An Adversarial Domain Adaptation Network For Cross-Domain Fine-Grained Recognition. WACV (2020)
Yuanyu Wan, Lijun Zhang
Projection-free Online Learning over Strongly Convex Sets. CoRR (2020)
Lijun Zhang
Online Learning in Changing Environments. IJCAI (2020)
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) (2020)
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 (2019)
Guanghui Wang, Shiyin Lu, Lijun Zhang
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. UAI (2019)
Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang
Multi-Objective Generalized Linear Bandits. CoRR (2019)
Lijun Zhang, Zhi-Hua Zhou
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate. COLT (2019)
Guanghui Wang, Shiyin Lu, Weiwei Tu, Lijun Zhang
SAdam: A Variant of Adam for Strongly Convex Functions. CoRR (2019)
Lijun Zhang, Guanghui Wang, Weiwei Tu, Zhi-Hua Zhou
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. CoRR (2019)
Shiyin Lu, Lijun Zhang
More Adaptive Algorithms for Tracking the Best Expert. CoRR (2019)
Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou
A simple homotopy proximal mapping algorithm for compressive sensing. Mach. Learn. 108 (6) (2019)
Guanghui Wang, Shiyin Lu, Lijun Zhang
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. CoRR (2019)
Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou
Adaptive Regret of Convex and Smooth Functions. CoRR (2019)
Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou
Adaptive Regret of Convex and Smooth Functions. ICML (2019)
Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards. ICML (2019)
Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
Prediction with Unpredictable Feature Evolution. CoRR (2019)
Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang
Stochastic Optimization for Non-convex Inf-Projection Problems. CoRR (2019)
Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang
Multi-Objective Generalized Linear Bandits. IJCAI (2019)
Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion. J. Mach. Learn. Res. 20 (2019)
Lijun Zhang, Zhi-Hua Zhou
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the O(1/T) Convergence Rate. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lijun Zhang