Lijun Zhang - RankMe

295 papers A* 102A 16B 2C 1Journal 152Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Building Autonomous GUI Navigation via Agentic-Q Estimation and Step-Wise Policy Optimization. CoRR Yibo Wang, Guangda Huzhang, Yuwei Hu, Yu Xia, Shiyin Lu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang
2026	J	`jnl`	Cooperative Bandit Algorithms With Optimal Regret and Communication Costs. IEEE Trans. Netw. Lin Yang, Xuchuang Wang, Haoxu Chen, Mohammad H. Hajiesmaili, Lijun Zhang, John C. S. Lui, Don Towsley
2026	J	`jnl`	Optimizing Unnormalized Statistical Models Through Compositional Optimization. IEEE Trans. Pattern Anal. Mach. Intell. Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang
2026	J	`jnl`	Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. ACM Trans. Knowl. Discov. Data Hui Guan, Umang Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, Xipeng Shen
2026	J	`jnl`	Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs. CoRR Yibo Wang, Hai-Long Sun, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang
2025	J	`jnl`	Attacking all tasks at once using adversarial examples in multi-task learning. Neurocomputing Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan
2025	J	`jnl`	Communication-Efficient Multi-Device Inference Acceleration for Transformer Models. CoRR Xiao Liu, Lijun Zhang, Deepak Ganesan, Hui Guan
2025	J	`jnl`	Continual Learning With Unknown Task Boundary. IEEE Trans. Neural Networks Learn. Syst. Xiaoxie Zhu, Jinfeng Yi, Lijun Zhang
2025	J	`jnl`	Continuous Subspace Optimization for Continual Learning. CoRR Quan Cheng, Yuanyu Wan, Lingyu Wu, Chenping Hou, Lijun Zhang
2025	J	`jnl`	Deep But Reliable: Advancing Multi-turn Reasoning for Thinking with Images. CoRR Wenhao Yang, Yu Xia, Jinlong Huang, Shiyin Lu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Yuanyu Wan, Lijun Zhang
2025	A*	`conf`	Dimension-Free Adaptive Subgradient Methods with Frequent Directions. ICML Sifan Yang, Yuanyu Wan, Peijia Li, Yibo Wang, Xiao Zhang, Zhewei Wei, Lijun Zhang
2025	J	`jnl`	Dual Adaptivity: Universal Algorithms for Minimizing the Adaptive Regret of Convex Functions. CoRR Lijun Zhang, Wenhao Yang, Guanghui Wang, Wei Jiang, Zhi-Hua Zhou
2025	J	`jnl`	Efficient Methods for Non-stationary Online Learning. J. Mach. Learn. Res. Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou
2025	J	`jnl`	Improved Analysis for Sign-based Methods with Momentum Updates. CoRR Wei Jiang, Dingzhi Yu, Sifan Yang, Wenhao Yang, Lijun Zhang
2025	J	`jnl`	Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound. J. Mach. Learn. Res. Bo Xue, Ji Cheng, Fei Liu, Yimu Wang, Lijun Zhang, Qingfu Zhang
2025	J	`jnl`	Mirror Descent Under Generalized Smoothness. CoRR Dingzhi Yu, Wei Jiang, Yuanyu Wan, Lijun Zhang
2025	A*	`conf`	On the Generalization of Feature Incremental Learning. IJCAI Chao Xu, Xijia Tang, Lijun Zhang, Chenping Hou
2025	A*	`conf`	One-step Label Shift Adaptation via Robust Weight Estimation. IJCAI Ruidong Fan, Xiao Ouyang, Tingjin Luo, Lijun Zhang, Chenping Hou
2025	J	`jnl`	Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting. CoRR Sifan Yang, Yuanyu Wan, Lijun Zhang
2025	J	`jnl`	Optimal and Efficient Algorithms for Decentralized Online Convex Optimization. J. Mach. Learn. Res. Yuanyu Wan, Tong Wei, Bo Xue, Mingli Song, Lijun Zhang
2025	J	`jnl`	Optimal large-scale stochastic optimization of NDCG surrogates for deep learning. Mach. Learn. Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Wei-Wei Tu, Lijun Zhang, Tianbao Yang
2025	J	`jnl`	PVBF: A Framework for Mitigating Parameter Variation Imbalance in Online Continual Learning. CoRR Ze Tao, Hao Deng, Mingqing Liu, Lijun Zhang, Shengjie Zhao
2025	J	`jnl`	PVBF: A framework for mitigating parameter variation imbalance in online continual learning. Neural Networks Zelin Tao, Hao Deng, Mingqing Liu, Lijun Zhang, Shengjie Zhao
2025	A*	`conf`	Revisiting Projection-Free Online Learning with Time-Varying Constraints. AAAI Yibo Wang, Yuanyu Wan, Lijun Zhang
2025	J	`jnl`	Revisiting Projection-Free Online Learning with Time-Varying Constraints. CoRR Yibo Wang, Yuanyu Wan, Lijun Zhang
2025	J	`jnl`	Revisiting Stochastic Multi-Level Compositional Optimization. IEEE Trans. Pattern Anal. Mach. Intell. Wei Jiang, Sifan Yang, Yibo Wang, Tianbao Yang, Lijun Zhang
2025	A*	`conf`	Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation. AAAI Yibo Wang, Yingchun Jian, Wenhao Yang, Shiyin Lu, Lei Shen, Bing Wang, Xiaoyi Zeng, Lijun Zhang
2025	J	`jnl`	Universal Online Convex Optimization Meets Second-order Bounds. J. Mach. Learn. Res. Lijun Zhang, Yibo Wang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
2024	J	`jnl`	A Tree-Structured Multitask Model Architectures Recommendation System. IEEE Trans. Neural Networks Learn. Syst. Lijun Zhang, Xiao Liu, Hui Guan
2024	A*	`conf`	Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions. NeurIPS Wei Jiang, Sifan Yang, Yibo Wang, Lijun Zhang
2024	J	`jnl`	Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions. CoRR Wei Jiang, Sifan Yang, Yibo Wang, Lijun Zhang
2024	J	`jnl`	Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. J. Mach. Learn. Res. Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
2024	A*	`conf`	Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees. NeurIPS Sijia Chen, Yibo Wang, Yi-Feng Wu, Qingguo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang
2024	J	`jnl`	Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees. CoRR Sijia Chen, Yibo Wang, Yi-Feng Wu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang
2024	A*	`conf`	Attack-Resilient Image Watermarking Using Stable Diffusion. NeurIPS Lijun Zhang, Xiao Liu, Antoni Viros Martin, Cindy Xiong Bearfield, Yuriy Brun, Hui Guan
2024	J	`jnl`	Efficient Algorithms for Empirical Group Distributional Robust Optimization and Beyond. CoRR Dingzhi Yu, Yunuo Cai, Wei Jiang, Lijun Zhang
2024	A*	`conf`	Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond. ICML Dingzhi Yu, Yunuo Cai, Wei Jiang, Lijun Zhang
2024	A*	`conf`	Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction. NeurIPS Wei Jiang, Sifan Yang, Wenhao Yang, Lijun Zhang
2024	J	`jnl`	Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction. CoRR Wei Jiang, Sifan Yang, Wenhao Yang, Lijun Zhang
2024	A*	`conf`	Efficient Stochastic Approximation of Minimax Excess Risk Optimization. ICML Lijun Zhang, Haomin Bai, Wei-Wei Tu, Ping Yang, Yao Hu
2024	A	`conf`	GMorph: Accelerating Multi-DNN Inference via Model Fusion. EuroSys Qizheng Yang, Tianyi Yang, Mingcan Xiang, Lijun Zhang, Haoliang Wang, Marco Serafini, Hui Guan
2024	A*	`conf`	High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails. ICML Langqi Liu, Yibo Wang, Lijun Zhang
2024	A*	`conf`	Improved Regret for Bandit Convex Optimization with Delayed Feedback. NeurIPS Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang
2024	J	`jnl`	Improved Regret for Bandit Convex Optimization with Delayed Feedback. CoRR Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang
2024	J	`jnl`	Information-Enhanced Graph Neural Network for Transcending Homophily Barriers. IEEE Access Xiao Liu, Lijun Zhang, Hui Guan
2024	A*	`conf`	Nearly Optimal Regret for Decentralized Online Convex Optimization. COLT Yuanyu Wan, Tong Wei, Mingli Song, Lijun Zhang
2024	J	`jnl`	Nearly Optimal Regret for Decentralized Online Convex Optimization. CoRR Yuanyu Wan, Tong Wei, Mingli Song, Lijun Zhang
2024	A*	`conf`	Non-stationary Online Convex Optimization with Arbitrary Delays. ICML Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang
2024	A*	`conf`	Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees. AAAI Yibo Wang, Wenhao Yang, Wei Jiang, Shiyin Lu, Bing Wang, Haihong Tang, Yuanyu Wan, Lijun Zhang
2024	A*	`conf`	Not All Embeddings are Created Equal: Towards Robust Cross-domain Recommendation via Contrastive Learning. WWW Wenhao Yang, Yingchun Jian, Yibo Wang, Shiyin Lu, Lei Shen, Bing Wang, Haihong Tang, Lijun Zhang
2024	A*	`conf`	Online Composite Optimization Between Stochastic and Adversarial Environments. NeurIPS Yibo Wang, Sijia Chen, Wei Jiang, Wenhao Yang, Yuanyu Wan, Lijun Zhang
2024	J	`jnl`	Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. J. Mach. Learn. Res. Sijia Chen, Yu-Jie Zhang, Wei-Wei Tu, Peng Zhao, Lijun Zhang
2024	A*	`conf`	Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization. ICML Wei Jiang, Sifan Yang, Wenhao Yang, Yibo Wang, Yuanyu Wan, Lijun Zhang
2024	J	`jnl`	Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization. CoRR Wei Jiang, Sifan Yang, Wenhao Yang, Yibo Wang, Yuanyu Wan, Lijun Zhang
2024	J	`jnl`	Robust Image Watermarking using Stable Diffusion. CoRR Lijun Zhang, Xiao Liu, Antoni Viros Martin, Cindy Xiong Bearfield, Yuriy Brun, Hui Guan
2024	A*	`conf`	Small-loss Adaptive Regret for Online Convex Optimization. ICML Wenhao Yang, Wei Jiang, Yibo Wang, Ping Yang, Yao Hu, Lijun Zhang
2024	—	`conf`	Structured Pruning for Multi-Task Deep Neural Networks. MIPR Siddhant Garg, Lijun Zhang, Hui Guan
2024	A*	`conf`	Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. NeurIPS Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan
2024	J	`jnl`	Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. CoRR Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan
2024	A*	`conf`	To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. ICML Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
2024	J	`jnl`	To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. CoRR Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
2024	A*	`conf`	Universal Online Convex Optimization with 1 Projection per Round. NeurIPS Wenhao Yang, Yibo Wang, Peng Zhao, Lijun Zhang
2024	J	`jnl`	Universal Online Convex Optimization with 1 Projection per Round. CoRR Wenhao Yang, Yibo Wang, Peng Zhao, Lijun Zhang
2023	J	`jnl`	An Alternative Hard-Parameter Sharing Paradigm for Multi-Domain Learning. IEEE Access Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan
2023	A*	`conf`	Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. ICML Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang
2023	J	`jnl`	Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. CoRR Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang
2023	J	`jnl`	Cooperative Multi-agent Bandits: Distributed Algorithms with Optimal Individual Regret and Constant Communication Costs. CoRR Lin Yang, Xuchuang Wang, Mohammad Hajiesmaili, Lijun Zhang, John C. S. Lui, Don Towsley
2023	A*	`conf`	Distributed Projection-Free Online Learning for Smooth and Convex Losses. AAAI Yibo Wang, Yuanyu Wan, Shimao Zhang, Lijun Zhang
2023	J	`jnl`	Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. CoRR Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan
2023	A*	`conf`	Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. NeurIPS Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang
2023	J	`jnl`	Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. CoRR Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang
2023	J	`jnl`	Efficient Methods for Non-stationary Online Learning. CoRR Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou
2023	J	`jnl`	Efficient Stochastic Approximation of Minimax Excess Risk Optimization. CoRR Lijun Zhang, Wei-Wei Tu
2023	A*	`conf`	Flow: Per-instance Personalized Federated Learning. NeurIPS Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan
2023	A*	`conf`	Improved Dynamic Regret for Online Frank-Wolfe. COLT Yuanyu Wan, Lijun Zhang, Mingli Song
2023	J	`jnl`	Improved Dynamic Regret for Online Frank-Wolfe. CoRR Yuanyu Wan, Lijun Zhang, Mingli Song
2023	A*	`conf`	Learning Unnormalized Statistical Models via Compositional Optimization. ICML Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang
2023	J	`jnl`	Learning Unnormalized Statistical Models via Compositional Optimization. CoRR Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang
2023	J	`jnl`	Non-stationary Online Convex Optimization with Arbitrary Delays. CoRR Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang
2023	J	`jnl`	Non-stationary Projection-free Online Learning with Dynamic and Adaptive Regret Guarantees. CoRR Yibo Wang, Wenhao Yang, Wei Jiang, Shiyin Lu, Bing Wang, Haihong Tang, Yuanyu Wan, Lijun Zhang
2023	A*	`conf`	Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. ICML Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang
2023	J	`jnl`	Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. CoRR Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang
2023	A*	`conf`	Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. ICML Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang
2023	J	`jnl`	Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. CoRR Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang
2023	A*	`conf`	Stochastic Approximation Approaches to Group Distributionally Robust Optimization. NeurIPS Lijun Zhang, Peng Zhao, Zhen-Hua Zhuang, Tianbao Yang, Zhi-Hua Zhou
2023	J	`jnl`	Stochastic Approximation Approaches to Group Distributionally Robust Optimization. CoRR Lijun Zhang, Peng Zhao, Tianbao Yang, Zhi-Hua Zhou
2023	A	`conf`	Stochastic Graphical Bandits with Heavy-Tailed Rewards. UAI Yutian Gou, Jinfeng Yi, Lijun Zhang
2023	J	`jnl`	Structured Pruning for Multi-Task Deep Neural Networks. CoRR Siddhant Garg, Lijun Zhang, Hui Guan
2022	A*	`conf`	A Simple yet Universal Strategy for Online Convex Optimization. ICML Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
2022	—	`conf`	A Tree-Structured Multi-Task Model Recommender. AutoML Lijun Zhang, Xiao Liu, Hui Guan
2022	J	`jnl`	A Tree-Structured Multi-Task Model Recommender. CoRR Lijun Zhang, Xiao Liu, Hui Guan
2022	—	`conf`	Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. PAKDD (1) Yingchun Jian, Jinfeng Yi, Lijun Zhang
2022	A*	`conf`	AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning. NeurIPS Lijun Zhang, Xiao Liu, Hui Guan
2022	J	`jnl`	Break the Wall Between Homophily and Heterophily for Graph Representation Learning. CoRR Xiao Liu, Lijun Zhang, Hui Guan
2022	J	`jnl`	Efficient Adaptive Online Learning via Frequent Directions. IEEE Trans. Pattern Anal. Mach. Intell. Yuanyu Wan, Lijun Zhang
2022	A*	`conf`	Efficient Methods for Non-stationary Online Learning. NeurIPS Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou
2022	A*	`conf`	Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. ICML Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang
2022	J	`jnl`	Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. CoRR Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang
2022	A	`conf`	Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. AISTATS Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang
2022	A*	`conf`	Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. NeurIPS Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang
2022	J	`jnl`	Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. CoRR Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang
2022	A	`conf`	Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization. WSDM Shiyin Lu, Yu-Hang Zhou, Jing-Cheng Shi, Wenya Zhu, Qingtao Yu, Qing-Guo Chen, Qing Da, Lijun Zhang
2022	—	`conf`	Non-stationary Dueling Bandits for Online Learning to Rank. APWeb/WAIM (2) Shiyin Lu, Yuan Miao, Ping Yang, Yao Hu, Lijun Zhang
2022	A*	`conf`	Online Frank-Wolfe with Arbitrary Delays. NeurIPS Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
2022	J	`jnl`	Online Frank-Wolfe with Unknown Delays. CoRR Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
2022	J	`jnl`	Online strongly convex optimization with unknown delays. Mach. Learn. Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
2022	A*	`conf`	Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. ICML Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang
2022	J	`jnl`	Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. CoRR Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang
2022	J	`jnl`	Prediction With Unpredictable Feature Evolution. IEEE Trans. Neural Networks Learn. Syst. Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
2022	J	`jnl`	Projection-free Distributed Online Learning with Sublinear Communication Complexity. J. Mach. Learn. Res. Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang
2022	A*	`conf`	Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. ICML Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang
2022	J	`jnl`	Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. CoRR Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang
2022	A	`conf`	Rethinking Hard-Parameter Sharing in Multi-Domain Learning. ICME Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan
2022	A*	`conf`	Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. NeurIPS Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
2022	J	`jnl`	Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. CoRR Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
2022	J	`jnl`	Strongly adaptive online learning over partial intervals. Sci. China Inf. Sci. Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
2021	J	`jnl`	A Simple yet Universal Strategy for Online Convex Optimization. CoRR Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang
2021	J	`jnl`	Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. CoRR Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
2021	A*	`conf`	Approximate Multiplication of Sparse Matrices with Limited Space. AAAI Yuanyu Wan, Lijun Zhang
2021	J	`jnl`	AutoMTL: A Programming Framework for Automated Multi-Task Learning. CoRR Lijun Zhang, Xiao Liu, Hui Guan
2021	J	`jnl`	Bandit Convex Optimization in Non-stationary Environments. J. Mach. Learn. Res. Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou
2021	J	`jnl`	Charging Task Scheduling for Directional Wireless Charger Networks. IEEE Trans. Mob. Comput. Haipeng Dai, Ke Sun, Alex X. Liu, Lijun Zhang, Jiaqi Zheng, Guihai Chen
2021	A*	`conf`	Deep Unified Cross-Modality Hashing by Pairwise Data Alignment. IJCAI Yimu Wang, Bo Xue, Quan Cheng, Yuhui Chen, Lijun Zhang
2021	A*	`conf`	Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. NeurIPS Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou
2021	—	`conf`	Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. L4DC Peng Zhao, Lijun Zhang
2021	J	`jnl`	Learning With Feature Evolvable Streams. IEEE Trans. Knowl. Data Eng. Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
2021	A	`conf`	Learning to Augment Imbalanced Data for Re-ranking Models. CIKM Zi-Hao Qiu, Ying-Chun Jian, Qing-Guo Chen, Lijun Zhang
2021	J	`jnl`	Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. CoRR Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang
2021	J	`jnl`	Non-stationary Linear Bandits Revisited. CoRR Peng Zhao, Lijun Zhang
2021	A*	`conf`	Online Convex Optimization with Continuous Switching Constraint. NeurIPS Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang
2021	J	`jnl`	Online Convex Optimization with Continuous Switching Constraint. CoRR Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang
2021	J	`jnl`	Online Strongly Convex Optimization with Unknown Delays. CoRR Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
2021	J	`jnl`	Projection-free Distributed Online Learning with Strongly Convex Losses. CoRR Yuanyu Wan, Guanghui Wang, Lijun Zhang
2021	A*	`conf`	Projection-free Online Learning in Dynamic Environments. AAAI Yuanyu Wan, Bo Xue, Lijun Zhang
2021	A*	`conf`	Projection-free Online Learning over Strongly Convex Sets. AAAI Yuanyu Wan, Lijun Zhang
2021	A*	`conf`	Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. ICDM Hui Guan, Umana Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, Xipeng Shen
2021	J	`jnl`	Rethinking Hard-Parameter Sharing in Multi-Task Learning. CoRR Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan
2021	J	`jnl`	Reuse-centric k-means configuration. Inf. Syst. Lijun Zhang, Hui Guan, Yufei Ding, Xipeng Shen, Hamid Krim
2021	A*	`conf`	Revisiting Smoothed Online Learning. NeurIPS Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang
2021	J	`jnl`	Revisiting Smoothed Online Learning. CoRR Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang
2021	A*	`conf`	Stochastic Bandits with Graph Feedback in Non-Stationary Environments. AAAI Shiyin Lu, Yao Hu, Lijun Zhang
2021	A*	`conf`	Stochastic Graphical Bandits with Adversarial Corruptions. AAAI Shiyin Lu, Guanghui Wang, Lijun Zhang
2021	J	`jnl`	Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression. CoRR Yuezhou Sun, Wenlong Zhao, Lijun Zhang, Xiao Liu, Hui Guan, Matei Zaharia
2020	A	`conf`	A Simple Approach for Non-stationary Linear Bandits. AISTATS Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou
2020	J	`jnl`	Accelerating adaptive online learning by matrix approximation. Int. J. Data Sci. Anal. Yuanyu Wan, Lijun Zhang
2020	A*	`conf`	Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization. AAAI Guanghui Wang, Shiyin Lu, Yao Hu, Lijun Zhang
2020	A	`conf`	An Adversarial Domain Adaptation Network For Cross-Domain Fine-Grained Recognition. WACV Yimu Wang, Ren-Jie Song, Xiu-Shen Wei, Lijun Zhang
2020	J	`jnl`	Approximate Multiplication of Sparse Matrices with Limited Space. CoRR Yuanyu Wan, Lijun Zhang
2020	A	`conf`	Bandit Convex Optimization in Non-stationary Environments. AISTATS Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou
2020	A*	`conf`	Dynamic Regret of Convex and Smooth Functions. NeurIPS Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
2020	J	`jnl`	Dynamic Regret of Convex and Smooth Functions. CoRR Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou
2020	J	`jnl`	High-dimensional model recovery from random sketched data by exploring intrinsic sparsity. Mach. Learn. Tianbao Yang, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin
2020	J	`jnl`	Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. CoRR Peng Zhao, Lijun Zhang
2020	A	`conf`	Improving Multi-Scenario Learning to Rank in E-commerce by Exploiting Task Relationships in the Label Space. CIKM Pengcheng Li, Runze Li, Qing Da, Anxiang Zeng, Lijun Zhang
2020	A	`conf`	Minimizing Dynamic Regret and Adaptive Regret Simultaneously. AISTATS Lijun Zhang, Shiyin Lu, Tianbao Yang
2020	J	`jnl`	Minimizing Dynamic Regret and Adaptive Regret Simultaneously. CoRR Lijun Zhang, Shiyin Lu, Tianbao Yang
2020	A*	`conf`	Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. IJCAI Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang
2020	J	`jnl`	Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. CoRR Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang
2020	A*	`conf`	Online Learning in Changing Environments. IJCAI Lijun Zhang
2020	—	`conf`	Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search. PRCV (2) Yimu Wang, Xiu-Shen Wei, Bo Xue, Lijun Zhang
2020	A*	`conf`	Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity. ICML Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
2020	J	`jnl`	Projection-free Online Learning over Strongly Convex Sets. CoRR Yuanyu Wan, Lijun Zhang
2020	A*	`conf`	SAdam: A Variant of Adam for Strongly Convex Functions. ICLR Guanghui Wang, Shiyin Lu, Quan Cheng, Weiwei Tu, Lijun Zhang
2020	J	`jnl`	SID-NISM: A Self-supervised Low-light Image Enhancement Framework. CoRR Lijun Zhang, Xiao Liu, Erik G. Learned-Miller, Hui Guan
2020	A*	`conf`	Searching Privately by Imperceptible Lying: A Novel Private Hashing Method with Differential Privacy. ACM Multimedia Yimu Wang, Shiyin Lu, Lijun Zhang
2020	A*	`conf`	Stochastic Optimization for Non-convex Inf-Projection Problems. ICML Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang
2020	J	`jnl`	VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao
2019	J	`jnl`	A simple homotopy proximal mapping algorithm for compressive sensing. Mach. Learn. Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou
2019	A*	`conf`	Adaptive Regret of Convex and Smooth Functions. ICML Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou
2019	J	`jnl`	Adaptive Regret of Convex and Smooth Functions. CoRR Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou
2019	A	`conf`	Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. UAI Guanghui Wang, Shiyin Lu, Lijun Zhang
2019	J	`jnl`	Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. CoRR Guanghui Wang, Shiyin Lu, Lijun Zhang
2019	J	`jnl`	Bandit Convex Optimization in Non-stationary Environments. CoRR Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou
2019	J	`jnl`	Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. CoRR Lijun Zhang, Guanghui Wang, Weiwei Tu, Zhi-Hua Zhou
2019	—	`conf`	Generative Adversarial Network-based Image Super-Resolution with a Novel Quality Loss. ISPACS Xining Zhu, Lin Zhang, Lijun Zhang, Xiao Liu, Ying Shen, Shengjie Zhao
2019	A*	`conf`	Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. IJCAI Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang
2019	J	`jnl`	Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. CoRR Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang
2019	J	`jnl`	More Adaptive Algorithms for Tracking the Best Expert. CoRR Shiyin Lu, Lijun Zhang
2019	A*	`conf`	Multi-Objective Generalized Linear Bandits. IJCAI Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang
2019	J	`jnl`	Multi-Objective Generalized Linear Bandits. CoRR Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang
2019	A*	`conf`	Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards. ICML Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang
2019	J	`jnl`	Prediction with Unpredictable Feature Evolution. CoRR Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
2019	J	`jnl`	Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion. J. Mach. Learn. Res. Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2019	J	`jnl`	SAdam: A Variant of Adam for Strongly Convex Functions. CoRR Guanghui Wang, Shiyin Lu, Weiwei Tu, Lijun Zhang
2019	A*	`conf`	Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate. COLT Lijun Zhang, Zhi-Hua Zhou
2019	J	`jnl`	Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the O(1/T) Convergence Rate. CoRR Lijun Zhang, Zhi-Hua Zhou
2019	J	`jnl`	Stochastic Optimization for Non-convex Inf-Projection Problems. CoRR Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang
2019	J	`jnl`	Stochastic Primal-Dual Algorithms with Faster Convergence than O(1/√T) for Problems without Bilinear Structure. CoRR Yan Yan, Yi Xu, Qihang Lin, Lijun Zhang, Tianbao Yang
2019	A*	`conf`	Zero-Shot Restoration of Back-lit Images Using Deep Internal Learning. ACM Multimedia Lin Zhang, Lijun Zhang, Xiao Liu, Ying Shen, Shaoming Zhang, Shengjie Zhao
2018	A	`conf`	A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer. AISTATS Tianbao Yang, Zhe Li, Lijun Zhang
2018	—	`conf`	Accelerating Adaptive Online Learning by Matrix Approximation. PAKDD (2) Yuanyu Wan, Lijun Zhang
2018	A*	`conf`	Adaptive Online Learning in Dynamic Environments. NeurIPS Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou
2018	J	`jnl`	Adaptive Online Learning in Dynamic Environments. CoRR Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou
2018	B	`conf`	Charging Task Scheduling for Directional Wireless Charger Networks. ICPP Haipeng Dai, Ke Sun, Alex X. Liu, Lijun Zhang, Jiaqi Zheng, Guihai Chen
2018	A*	`conf`	Dynamic Regret of Strongly Adaptive Methods. ICML Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2018	A*	`conf`	Efficient Adaptive Online Learning via Frequent Directions. IJCAI Yuanyu Wan, Nan Wei, Lijun Zhang
2018	A*	`conf`	Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. NeurIPS Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang
2018	J	`jnl`	Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. CoRR Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang
2018	A	`conf`	Image Exposure Assessment: A Benchmark and a Deep Convolutional Neural Networks Based Model. ICME Lijun Zhang, Lin Zhang, Xiao Liu, Ying Shen, Dongqing Wang
2018	J	`jnl`	Matrix Completion from Non-Uniformly Sampled Entries. CoRR Yuanyu Wan, Jinfeng Yi, Lijun Zhang
2018	A*	`conf`	Minimizing Adaptive Regret with One Gradient per Iteration. IJCAI Guanghui Wang, Dakuan Zhao, Lijun Zhang
2018	A*	`conf`	Query-Efficient Black-Box Attack by Active Learning. ICDM Pengcheng Li, Jinfeng Yi, Lijun Zhang
2018	J	`jnl`	Query-Efficient Black-Box Attack by Active Learning. CoRR Pengcheng Li, Jinfeng Yi, Lijun Zhang
2018	J	`jnl`	VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao
2018	A*	`conf`	\ell_1-regression with Heavy-tailed Distributions. NeurIPS Lijun Zhang, Zhi-Hua Zhou
2018	J	`jnl`	𝓁 CoRR Lijun Zhang, Zhi-Hua Zhou
2017	A*	`conf`	A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates. ICML Tianbao Yang, Qihang Lin, Lijun Zhang
2017	J	`jnl`	A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer. CoRR Tianbao Yang, Zhe Li, Lijun Zhang
2017	A*	`conf`	A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis. AAAI Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin
2017	A*	`conf`	Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee. AAAI Yi Xu, Haiqin Yang, Lijun Zhang, Tianbao Yang
2017	A*	`conf`	Efficient Stochastic Optimization for Low-Rank Distance Metric Learning. AAAI Jie Zhang, Lijun Zhang
2017	A*	`conf`	Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds. COLT Lijun Zhang, Tianbao Yang, Rong Jin
2017	J	`jnl`	Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n CoRR Lijun Zhang, Tianbao Yang, Rong Jin
2017	—	`conf`	Illumination Quality Assessment for Face Images: A Benchmark and a Convolutional Neural Networks Based Model. ICONIP (3) Lijun Zhang, Lin Zhang, Lida Li
2017	—	`conf`	Improved Dynamic Regret for Non-degenerate Functions. NIPS Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou
2017	—	`conf`	Learning with Feature Evolvable Streams. NIPS Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
2017	J	`jnl`	Learning with Feature Evolvable Streams. CoRR Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
2017	J	`jnl`	Non-redundant multiple clustering by nonnegative matrix factorization. Mach. Learn. Sen Yang, Lijun Zhang
2017	J	`jnl`	Positive-Unlabeled Demand-Aware Recommendation. CoRR Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li
2017	A*	`conf`	SVD-free Convex-Concave Approaches for Nuclear Norm Regularization. IJCAI Yichi Xiao, Zhe Li, Tianbao Yang, Lijun Zhang
2017	—	`conf`	Scalable Demand-Aware Recommendation. NIPS Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li
2017	A*	`conf`	Semi-Supervised Deep Hashing with a Bipartite Graph. IJCAI Xinyu Yan, Lijun Zhang, Wu-Jun Li
2017	J	`jnl`	Sparse Learning with Stochastic Composite Optimization. IEEE Trans. Pattern Anal. Mach. Intell. Weizhong Zhang, Lijun Zhang, Zhongming Jin, Rong Jin, Deng Cai, Xuelong Li, Ronghua Liang, Xiaofei He
2017	A*	`conf`	Storage Fit Learning with Unlabeled Data. IJCAI Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
2017	J	`jnl`	Strongly Adaptive Regret Implies Optimally Dynamic Regret. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2016	J	`jnl`	A-Optimal Projection for Image Representation. IEEE Trans. Pattern Anal. Mach. Intell. Xiaofei He, Chiyuan Zhang, Lijun Zhang, Xuelong Li
2016	A*	`conf`	Accelerated Sparse Linear Regression via Random Projection. AAAI Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He
2016	J	`jnl`	Efficient Non-oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee. CoRR Yi Xu, Haiqin Yang, Lijun Zhang, Tianbao Yang
2016	A*	`conf`	Fast and Accurate Refined Nyström-Based Kernel SVM. AAAI Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin
2016	J	`jnl`	Graph Regularized Feature Selection with Data Reconstruction. IEEE Trans. Knowl. Data Eng. Zhou Zhao, Xiaofei He, Deng Cai, Lijun Zhang, Wilfred Ng, Yueting Zhuang
2016	J	`jnl`	Improved dynamic regret for non-degeneracy functions. CoRR Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou
2016	A*	`conf`	Online Stochastic Linear Optimization under One-bit Feedback. ICML Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-Hua Zhou
2016	J	`jnl`	Online kernel learning with nearly constant support vectors. Neurocomputing Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang
2016	A	`conf`	Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. UAI Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang
2016	B	`conf`	Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach. ALT Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2016	A*	`conf`	Stochastic Optimization for Kernel PCA. AAAI Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou
2016	A*	`conf`	Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. ICML Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi
2016	J	`jnl`	Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. CoRR Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi
2015	A	`conf`	A Simple Homotopy Algorithm for Compressive Sensing. AISTATS Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	A*	`conf`	An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints. KDD Jinfeng Yi, Lijun Zhang, Tianbao Yang, Wei Liu, Jun Wang
2015	A*	`conf`	An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection. ICML Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2015	J	`jnl`	Analysis of Nuclear Norm Regularization for Full-rank Matrix Completion. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	—	`conf`	Design and implementation of precise measuring method for the access time of embedded memory. ASICON Yuqing Hu, Lijun Zhang, Youzhong Li, Qixiao Zhang, Erliang Li, Wei Jiang
2015	J	`jnl`	Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). Mach. Learn. Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu
2015	J	`jnl`	Expert Finding for Question Answering via Graph Regularized Matrix Completion. IEEE Trans. Knowl. Data Eng. Zhou Zhao, Lijun Zhang, Xiaofei He, Wilfred Ng
2015	J	`jnl`	Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees. CoRR Tianbao Yang, Lijun Zhang, Qihang Lin, Rong Jin
2015	J	`jnl`	Graph-based local concept coordinate factorization. Knowl. Inf. Syst. Ping Li, Jiajun Bu, Lijun Zhang, Chun Chen
2015	A*	`conf`	Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. COLT Mehrdad Mahdavi, Lijun Zhang, Rong Jin
2015	J	`jnl`	Multi-View Concept Learning for Data Representation. IEEE Trans. Knowl. Data Eng. Ziyu Guan, Lijun Zhang, Jinye Peng, Jianping Fan
2015	A*	`conf`	Online Bandit Learning for a Special Class of Non-Convex Losses. AAAI Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Online Stochastic Linear Optimization under One-bit Feedback. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Stochastic Proximal Gradient Descent for Nuclear Norm Regularization. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	A*	`conf`	Theory of Dual-sparse Regularized Randomized Reduction. ICML Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2015	J	`jnl`	Theory of Dual-sparse Regularized Randomized Reduction. CoRR Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2015	J	`jnl`	Towards Making High Dimensional Distance Metric Learning Practical. CoRR Qi Qian, Rong Jin, Lijun Zhang, Shenghuo Zhu
2015	J	`jnl`	Unsupervised document summarization from data reconstruction perspective. Neurocomputing Zhanying He, Chun Chen, Jiajun Bu, Can Wang, Lijun Zhang, Deng Cai, Xiaofei He
2014	J	`jnl`	A Simple Homotopy Proximal Mapping for Compressive Sensing. CoRR Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2014	A*	`conf`	A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data. ICML Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil K. Jain
2014	J	`jnl`	Binary Excess Risk for Smooth Convex Surrogates. CoRR Mehrdad Mahdavi, Lijun Zhang, Rong Jin
2014	A*	`conf`	Efficient Algorithms for Robust One-bit Compressive Sensing. ICML Lijun Zhang, Jinfeng Yi, Rong Jin
2014	J	`jnl`	Random Projections for Classification: A Recovery Approach. IEEE Trans. Inf. Theory Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu
2014	A*	`conf`	Sparse Learning for Stochastic Composite Optimization. AAAI Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He
2013	J	`jnl`	Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD) CoRR Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu
2013	J	`jnl`	Efficient Stochastic Gradient Descent for Strongly Convex Optimization CoRR Tianbao Yang, Lijun Zhang
2013	J	`jnl`	Improving the Minimax Rate of Active Learning. CoRR Lijun Zhang, Mehrdad Mahdavi, Rong Jin
2013	—	`conf`	Linear Convergence with Condition Number Independent Access of Full Gradients. NIPS Lijun Zhang, Mehrdad Mahdavi, Rong Jin
2013	—	`conf`	Mixed Optimization for Smooth Functions. NIPS Mehrdad Mahdavi, Lijun Zhang, Rong Jin
2013	J	`jnl`	O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He
2013	—	`conf`	O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions. ICML (3) Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He
2013	—	`conf`	Online Kernel Learning with a Near Optimal Sparsity Bound. ICML (3) Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He
2013	A*	`conf`	Recovering the Optimal Solution by Dual Random Projection. COLT Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu
2013	—	`conf`	Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. ICML (3) Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil K. Jain
2012	J	`jnl`	A Unified Feature and Instance Selection Framework Using Optimum Experimental Design. IEEE Trans. Image Process. Lijun Zhang, Chun Chen, Jiajun Bu, Xiaofei He
2012	A*	`conf`	Document Summarization Based on Data Reconstruction. AAAI Zhanying He, Chun Chen, Jiajun Bu, Can Wang, Lijun Zhang, Deng Cai, Xiaofei He
2012	A*	`conf`	Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression. AAAI Lijun Zhang, Rong Jin, Chun Chen, Jiajun Bu, Xiaofei He
2012	J	`jnl`	Locally Discriminative Coclustering. IEEE Trans. Knowl. Data Eng. Lijun Zhang, Chun Chen, Jiajun Bu, Zhengguang Chen, Deng Cai, Jiawei Han
2012	J	`jnl`	Locally discriminative topic modeling. Pattern Recognit. Hao Wu, Jiajun Bu, Chun Chen, Jianke Zhu, Lijun Zhang, Haifeng Liu, Can Wang, Deng Cai
2012	J	`jnl`	Multiple Kernel Learning from Noisy Labels by Stochastic Programming CoRR Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou
2012	A*	`conf`	Multiple Kernel Learning from Noisy Labels by Stochastic Programming. ICML Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou
2012	J	`jnl`	Recovering Optimal Solution by Dual Random Projection CoRR Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang
2011	J	`jnl`	Active Learning Based on Locally Linear Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. Lijun Zhang, Chun Chen, Jiajun Bu, Deng Cai, Xiaofei He, Thomas S. Huang
2011	J	`jnl`	Graph Regularized Sparse Coding for Image Representation. IEEE Trans. Image Process. Miao Zheng, Jiajun Bu, Chun Chen, Can Wang, Lijun Zhang, Guang Qiu, Deng Cai
2011	—	`conf`	Word line boost and read SA PMOS compensation (SAPC) for ROM in 55nm CMOS. ASICON Ruifeng Huang, Jianbin Zheng, Lijun Zhang, Zhaoyong Zhang, Hao Wu, Yue Yu
2010	C	`conf`	A Metric for Measuring Members' Contribution to Information Propagation in Social Network Sites. APWeb Jiajia Zheng, Wei Chen, Lijun Zhang, Jiajun Bu, Chun Chen
2010	J	`jnl`	Constrained Laplacian Eigenmap for dimensionality reduction. Neurocomputing Chun Chen, Lijun Zhang, Jiajun Bu, Can Wang, Wei Chen
2010	A*	`conf`	Discriminative codeword selection for image representation. ACM Multimedia Lijun Zhang, Chun Chen, Jiajun Bu, Zhengguang Chen, Shulong Tan, Xiaofei He
2010	A*	`conf`	G-Optimal Design with Laplacian Regularization. AAAI Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, Lijun Zhang, Cheng Zhang
2010	A*	`conf`	Modeling Dynamic Multi-Topic Discussions in Online Forums. AAAI Hao Wu, Jiajun Bu, Chun Chen, Can Wang, Guang Qiu, Lijun Zhang, Jianfeng Shen
2010	A*	`conf`	Music recommendation by unified hypergraph: combining social media information and music content. ACM Multimedia Jiajun Bu, Shulong Tan, Chun Chen, Can Wang, Hao Wu, Lijun Zhang, Xiaofei He
2010	J	`jnl`	Online detection of bursty events and their evolution in news streams. J. Zhejiang Univ. Sci. C Wei Chen, Chun Chen, Lijun Zhang, Can Wang, Jiajun Bu
2010	—	`conf`	Topic Decomposition and Summarization. PAKDD (1) Wei Chen, Can Wang, Chun Chen, Lijun Zhang, Jiajun Bu
2009	A*	`conf`	Convex experimental design using manifold structure for image retrieval. ACM Multimedia Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng Cai, Xiaofei He
2008	—	`conf`	Pervasive Web News Recommendation for Visually Impaired People. Web Intelligence/IAT Workshops Wei Chen, Lijun Zhang, Can Wang, Chun Chen, Jiajun Bu
2007	—	`conf`	User Modeling for Recommendation in Blogspace. Web Intelligence/IAT Workshops Kangmiao Liu, Wei Chen, Jiajun Bu, Chun Chen, Lijun Zhang