Zhang, Lijun

166 publications

NeurIPS 2025 Analyzing the Power of Chain of Thought Through Memorization Capabilities Lijia Yu, Xiao-Shan Gao, Lijun Zhang

NeurIPS 2025 Continuous Subspace Optimization for Continual Learning Quan Cheng, Yuanyu Wan, Lingyu Wu, Chenping Hou, Lijun Zhang

NeurIPS 2025 CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment Qinfeng Li, Tianyue Luo, Xuhong Zhang, Yangfan Xie, Zhiqiang Shen, Lijun Zhang, Yier Jin, Hao Peng, Xinkui Zhao, XianWei Zhu, Jianwei Yin

ICML 2025 Dimension-Free Adaptive Subgradient Methods with Frequent Directions Sifan Yang, Yuanyu Wan, Peijia Li, Yibo Wang, Xiao Zhang, Zhewei Wei, Lijun Zhang

CVPR 2025 Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan

JMLR 2025 Efficient Methods for Non-Stationary Online Learning Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou

ICCV 2025 External Knowledge Injection for CLIP-Based Class-Incremental Learning Da-Wei Zhou, Kai-Wen Li, Jingyi Ning, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan

ICLR 2025 Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power Lijia Yu, Yibo Miao, Yifan Zhu, Xiao-Shan Gao, Lijun Zhang

JMLR 2025 Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound Bo Xue, Ji Cheng, Fei Liu, Yimu Wang, Lijun Zhang, Qingfu Zhang

CVPR 2025 Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding Wei Suo, Lijun Zhang, Mengyang Sun, Lin Yuanbo Wu, Peng Wang, Yanning Zhang

IJCAI 2025 On the Generalization of Feature Incremental Learning Chao Xu, Xijia Tang, Lijun Zhang, Chenping Hou

IJCAI 2025 One-Step Label Shift Adaptation via Robust Weight Estimation Ruidong Fan, Xiao Ouyang, Tingjin Luo, Lijun Zhang, Chenping Hou

AAAI 2025 Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting Sifan Yang, Yuanyu Wan, Lijun Zhang

MLJ 2025 Optimal Large-Scale Stochastic Optimization of NDCG Surrogates for Deep Learning Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Wei-Wei Tu, Lijun Zhang, Tianbao Yang

JMLR 2025 Optimal and Efficient Algorithms for Decentralized Online Convex Optimization Yuanyu Wan, Tong Wei, Bo Xue, Mingli Song, Lijun Zhang

AAAI 2025 Revisiting Projection-Free Online Learning with Time-Varying Constraints Yibo Wang, Yuanyu Wan, Lijun Zhang

NeurIPS 2025 Risk-Aware Direct Preference Optimization Under Nested Risk Measure Lijun Zhang, Lin Li, Yajie Qi, Huizhong Song, Yaodong Yang, Jun Wang, Wei Wei

NeurIPS 2025 SPACE: Noise Contrastive Estimation Stabilizes Self-Play Fine-Tuning for Large Language Models Yibo Wang, Guangda Huzhang, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang

NeurIPS 2025 SeCon-RAG: A Two-Stage Semantic Filtering and Conflict-Free Framework for Trustworthy RAG Xiaonan Si, Meilin Zhu, Simeng Qin, Lijia Yu, Lijun Zhang, Shuaitong Liu, Xinfeng Li, Ranjie Duan, Yang Liu, Xiaojun Jia

IJCAI 2025 Smoothed Online Convex Optimization with Delayed Feedback Sifan Yang, Wenhao Yang, Wei Jiang, Yuanyu Wan, Lijun Zhang

AAAI 2025 Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation Yibo Wang, Yingchun Jian, Wenhao Yang, Shiyin Lu, Lei Shen, Bing Wang, Xiaoyi Zeng, Lijun Zhang

AAAI 2025 Training Verification-Friendly Neural Networks via Neuron Behavior Consistency Zongxin Liu, Zhe Zhao, Fu Song, Jun Sun, Pengfei Yang, Xiaowei Huang, Lijun Zhang

NeurIPS 2025 Triplets Better than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs Yibo Wang, Hai-Long Sun, Guangda Huzhang, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang

JMLR 2025 Universal Online Convex Optimization Meets Second-Order Bounds Lijun Zhang, Yibo Wang, Guanghui Wang, Jinfeng Yi, Tianbao Yang

NeurIPS 2024 Adaptive Variance Reduction for Stochastic Optimization Under Weaker Assumptions Wei Jiang, Sifan Yang, Yibo Wang, Lijun Zhang

JMLR 2024 Adaptivity and Non-Stationarity: Problem-Dependent Dynamic Regret for Online Convex Optimization Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou

NeurIPS 2024 Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees Sijia Chen, Yibo Wang, Yi-Feng Wu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang

ECCV 2024 Asynchronous Large Language Model Enhanced Planner for Autonomous Driving Yuan Chen, Zi-han Ding, Ziqin Wang, Yan Wang, Lijun Zhang, Si Liu

NeurIPS 2024 Attack-Resilient Image Watermarking Using Stable Diffusion Lijun Zhang, Xiao Liu, Antoni Viros Martin, Cindy Xiong Bearfield, Yuriy Brun, Hui Guan

CVPR 2024 CricaVPR: Cross-Image Correlation-Aware Representation Learning for Visual Place Recognition Feng Lu, Xiangyuan Lan, Lijun Zhang, Dongmei Jiang, Yaowei Wang, Chun Yuan

AAAI 2024 Deep Homography Estimation for Visual Place Recognition Feng Lu, Shuting Dong, Lijun Zhang, Bingxi Liu, Xiangyuan Lan, Dongmei Jiang, Chun Yuan

AAAI 2024 Deep Semantic Graph Transformer for Multi-View 3D Human Pose Estimation Lijun Zhang, Kangkang Zhou, Feng Lu, Xiang-Dong Zhou, Yu Shi

ICML 2024 Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond Dingzhi Yu, Yunuo Cai, Wei Jiang, Lijun Zhang

NeurIPS 2024 Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction Wei Jiang, Sifan Yang, Wenhao Yang, Lijun Zhang

ICML 2024 Efficient Stochastic Approximation of Minimax Excess Risk Optimization Lijun Zhang, Haomin Bai, Wei-Wei Tu, Ping Yang, Yao Hu

NeurIPS 2024 Generalizablity of Memorization Neural Network Lijia Yu, Xiao-Shan Gao, Lijun Zhang, Yibo Miao

ICML 2024 Generalization Bound and New Algorithm for Clean-Label Backdoor Attack Lijia Yu, Shuang Liu, Yibo Miao, Xiao-Shan Gao, Lijun Zhang

NeurIPS 2024 Improved Regret for Bandit Convex Optimization with Delayed Feedback Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang

COLT 2024 Nearly Optimal Regret for Decentralized Online Convex Optimization Yuanyu Wan, Tong Wei, Mingli Song, Lijun Zhang

ICML 2024 Non-Stationary Online Convex Optimization with Arbitrary Delays Yuanyu Wan, Chang Yao, Mingli Song, Lijun Zhang

AAAI 2024 Non-Stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees Yibo Wang, Wenhao Yang, Wei Jiang, Shiyin Lu, Bing Wang, Haihong Tang, Yuanyu Wan, Lijun Zhang

NeurIPS 2024 Online Composite Optimization Between Stochastic and Adversarial Environments Yibo Wang, Sijia Chen, Wei Jiang, Wenhao Yang, Yuanyu Wan, Lijun Zhang

NeurIPS 2024 Online Non-Convex Learning in Dynamic Environments Zhipan Xu, Lijun Zhang

ICLR 2024 Optimal Robust Memorization with ReLU Neural Networks Lijia Yu, Xiao-Shan Gao, Lijun Zhang

JMLR 2024 Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization Sijia Chen, Yu-Jie Zhang, Wei-Wei Tu, Peng Zhao, Lijun Zhang

ECCV 2024 Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors Tao Lin, Lijia Yu, Gaojie Jin, Renjue Li, Peng Wu, Lijun Zhang

ICML 2024 Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization Wei Jiang, Sifan Yang, Wenhao Yang, Yibo Wang, Yuanyu Wan, Lijun Zhang

NeurIPS 2024 Scalable Constrained Policy Optimization for Safe Multi-Agent Reinforcement Learning Lijun Zhang, Lin Li, Wei Wei, Huizhong Song, Yaodong Yang, Jiye Liang

ICML 2024 Small-Loss Adaptive Regret for Online Convex Optimization Wenhao Yang, Wei Jiang, Yibo Wang, Ping Yang, Yao Hu, Lijun Zhang

NeurIPS 2024 SuperVLAD: Compact and Robust Image Descriptors for Visual Place Recognition Feng Lu, Xinyao Zhang, Canming Ye, Shuting Dong, Lijun Zhang, Xiangyuan Lan, Chun Yuan

NeurIPS 2024 Thinking Forward: Memory-Efficient Federated Finetuning of Language Models Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan

ICML 2024 To Cool or Not to Cool? Temperature Network Meets Large Foundation Models via DRO Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang

ICLR 2024 Towards Seamless Adaptation of Pre-Trained Models for Visual Place Recognition Feng Lu, Lijun Zhang, Xiangyuan Lan, Shuting Dong, Yaowei Wang, Chun Yuan

NeurIPS 2024 Universal Online Convex Optimization with $1$ Projection per Round Wenhao Yang, Yibo Wang, Peng Zhao, Lijun Zhang

ICML 2023 Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang

AAAI 2023 Distributed Projection-Free Online Learning for Smooth and Convex Losses Yibo Wang, Yuanyu Wan, Shimao Zhang, Lijun Zhang

NeurIPS 2023 Efficient Algorithms for Generalized Linear Bandits with Heavy-Tailed Rewards Bo Xue, Yimu Wang, Yuanyu Wan, Jinfeng Yi, Lijun Zhang

NeurIPS 2023 Flow: Per-Instance Personalized Federated Learning Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan

COLT 2023 Improved Dynamic Regret for Online Frank-Wolfe Yuanyu Wan, Lijun Zhang, Mingli Song

ICML 2023 Learning Unnormalized Statistical Models via Compositional Optimization Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang

IJCAI 2023 Model Predictive Control with Reach-Avoid Analysis Dejin Ren, Wanli Lu, Jidong Lv, Lijun Zhang, Bai Xue

ICML 2023 Not All Semantics Are Created Equal: Contrastive Self-Supervised Learning with Automatic Temperature Individualization Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang

ICML 2023 Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang

ICML 2023 Set-Membership Belief State-Based Reinforcement Learning for POMDPs Wei Wei, Lijun Zhang, Lin Li, Huizhong Song, Jiye Liang

NeurIPS 2023 Stochastic Approximation Approaches to Group Distributionally Robust Optimization Lijun Zhang, Peng Zhao, Zhen-Hua Zhuang, Tianbao Yang, Zhi-Hua Zhou

UAI 2023 Stochastic Graphical Bandits with Heavy-Tailed Rewards Yutian Gou, Jinfeng Yi, Lijun Zhang

ICCV 2023 TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models Liang Zhang, Nathaniel Xu, Pengfei Yang, Gaojie Jin, Cheng-Chao Huang, Lijun Zhang

AISTATS 2022 Momentum Accelerates the Convergence of Stochastic AUPRC Maximization Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang

ICML 2022 A Simple yet Universal Strategy for Online Convex Optimization Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang

AutoML 2022 A Tree-Structured Multi-Task Model Recommender Lijun Zhang, Xiao Liu, Hui Guan

NeurIPS 2022 AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning Lijun Zhang, Xiao Liu, Hui Guan

NeurIPS 2022 Efficient Methods for Non-Stationary Online Learning Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou

ICML 2022 Large-Scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Lijun Zhang, Tianbao Yang

NeurIPS 2022 Multi-Block-Single-Probe Variance Reduced Estimator for Coupled Compositional Optimization Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang

NeurIPS 2022 Online Frank-Wolfe with Arbitrary Delays Yuanyu Wan, Wei-Wei Tu, Lijun Zhang

MLJ 2022 Online Strongly Convex Optimization with Unknown Delays Yuanyu Wan, Wei-Wei Tu, Lijun Zhang

ICML 2022 Optimal Algorithms for Stochastic Multi-Level Compositional Optimization Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang

JMLR 2022 Projection-Free Distributed Online Learning with Sublinear Communication Complexity Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang

ICML 2022 Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang

NeurIPS 2022 Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang

TMLR 2022 Weight Expansion: A New Perspective on Dropout and Generalization Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang

AAAI 2021 Approximate Multiplication of Sparse Matrices with Limited Space Yuanyu Wan, Lijun Zhang

JMLR 2021 Bandit Convex Optimization in Non-Stationary Environments Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou

IJCAI 2021 Deep Unified Cross-Modality Hashing by Pairwise Data Alignment Yimu Wang, Bo Xue, Quan Cheng, Yuhui Chen, Lijun Zhang

NeurIPS 2021 Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou

ICCV 2021 HRegNet: A Hierarchical Network for Large-Scale Outdoor LiDAR Point Cloud Registration Fan Lu, Guang Chen, Yinlong Liu, Lijun Zhang, Sanqing Qu, Shu Liu, Rongqi Gu

L4DC 2021 Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions Peng Zhao, Lijun Zhang

NeurIPS 2021 Online Convex Optimization with Continuous Switching Constraint Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang

AAAI 2021 Projection-Free Online Learning in Dynamic Environments Yuanyu Wan, Bo Xue, Lijun Zhang

AAAI 2021 Projection-Free Online Learning over Strongly Convex Sets Yuanyu Wan, Lijun Zhang

NeurIPS 2021 Revisiting Smoothed Online Learning Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang

AAAI 2021 Stochastic Bandits with Graph Feedback in Non-Stationary Environments Shiyin Lu, Yao Hu, Lijun Zhang

AAAI 2021 Stochastic Graphical Bandits with Adversarial Corruptions Shiyin Lu, Guanghui Wang, Lijun Zhang

IJCAI 2021 Synthesizing Good-Enough Strategies for LTLf Specifications Yong Li, Andrea Turrini, Moshe Y. Vardi, Lijun Zhang

AISTATS 2020 A Simple Approach for Non-Stationary Linear Bandits Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou

AAAI 2020 Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization Guanghui Wang, Shiyin Lu, Yao Hu, Lijun Zhang

WACV 2020 An Adversarial Domain Adaptation Network for Cross-Domain Fine-Grained Recognition Yimu Wang, Renjie Song, Xiu-Shen Wei, Lijun Zhang

AISTATS 2020 Bandit Convex Optimization in Non-Stationary Environments Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou

NeurIPS 2020 Dynamic Regret of Convex and Smooth Functions Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou

MLJ 2020 High-Dimensional Model Recovery from Random Sketched Data by Exploring Intrinsic Sparsity Tianbao Yang, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin

NeurIPS 2020 How Does Weight Correlation Affect Generalisation Ability of Deep Neural Networks? Gaojie Jin, Xinping Yi, Liang Zhang, Lijun Zhang, Sven Schewe, Xiaowei Huang

AISTATS 2020 Minimizing Dynamic Regret and Adaptive Regret Simultaneously Lijun Zhang, Shiyin Lu, Tianbao Yang

IJCAI 2020 Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang

IJCAI 2020 Online Learning in Changing Environments Lijun Zhang

ICML 2020 Projection-Free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity Yuanyu Wan, Wei-Wei Tu, Lijun Zhang

ICLR 2020 SAdam: A Variant of Adam for Strongly Convex Functions Guanghui Wang, Shiyin Lu, Weiwei Tu, Lijun Zhang

ICML 2020 Stochastic Optimization for Non-Convex Inf-Projection Problems Yan Yan, Yi Xu, Lijun Zhang, Wang Xiaoyu, Tianbao Yang

ICCVW 2019 3D Face Shape Regression from 2D Videos with Multi-Reconstruction and Mesh Retrieval Xiaohu Shao, Jiangjing Lyu, Junliang Xing, Lijun Zhang, Xiaobo Li, Xiangdong Zhou, Yu Shi

MLJ 2019 A Simple Homotopy Proximal Mapping Algorithm for Compressive Sensing Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou

ICML 2019 Adaptive Regret of Convex and Smooth Functions Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou

UAI 2019 Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization Guanghui Wang, Shiyin Lu, Lijun Zhang

IJCAI 2019 Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss Pengcheng Li, Jinfeng Yi, Bowen Zhou, Lijun Zhang

IJCAI 2019 Multi-Objective Generalized Linear Bandits Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang

ICML 2019 Optimal Algorithms for Lipschitz Bandits with Heavy-Tailed Rewards Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang

JMLR 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

COLT 2019 Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate Lijun Zhang, Zhi-Hua Zhou

NeurIPS 2018 $\ell_1$-Regression with Heavy-Tailed Distributions Lijun Zhang, Zhi-Hua Zhou

AISTATS 2018 A Simple Analysis for Exp-Concave Empirical Minimization with Arbitrary Convex Regularizer Tianbao Yang, Zhe Li, Lijun Zhang

NeurIPS 2018 Adaptive Online Learning in Dynamic Environments Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou

ICML 2018 Dynamic Regret of Strongly Adaptive Methods Lijun Zhang, Tianbao Yang, Jin, Zhi-Hua Zhou

IJCAI 2018 Efficient Adaptive Online Learning via Frequent Directions Yuanyu Wan, Nan Wei, Lijun Zhang

NeurIPS 2018 Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang

IJCAI 2018 Minimizing Adaptive Regret with One Gradient per Iteration Guanghui Wang, Dakuan Zhao, Lijun Zhang

IJCAI 2018 Model Checking Probabilistic Epistemic Logic for Probabilistic Multiagent Systems Chen Fu, Andrea Turrini, Xiaowei Huang, Lei Song, Yuan Feng, Lijun Zhang

ICML 2017 A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates Tianbao Yang, Qihang Lin, Lijun Zhang

AAAI 2017 A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin

AAAI 2017 Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee Yi Xu, Haiqin Yang, Lijun Zhang, Tianbao Yang

AAAI 2017 Efficient Stochastic Optimization for Low-Rank Distance Metric Learning Jie Zhang, Lijun Zhang

COLT 2017 Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-Type of Risk Bounds Lijun Zhang, Tianbao Yang, Rong Jin

NeurIPS 2017 Improved Dynamic Regret for Non-Degenerate Functions Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

NeurIPS 2017 Learning with Feature Evolvable Streams Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou

MLJ 2017 Non-Redundant Multiple Clustering by Nonnegative Matrix Factorization Sen Yang, Lijun Zhang

IJCAI 2017 SVD-Free Convex-Concave Approaches for Nuclear Norm Regularization Yichi Xiao, Zhe Li, Tianbao Yang, Lijun Zhang

NeurIPS 2017 Scalable Demand-Aware Recommendation Jinfeng Yi, Cho-Jui Hsieh, Kush R Varshney, Lijun Zhang, Yao Li

IJCAI 2017 Semi-Supervised Deep Hashing with a Bipartite Graph Xinyu Yan, Lijun Zhang, Wu-Jun Li

IJCAI 2017 Storage Fit Learning with Unlabeled Data Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou

AAAI 2016 Accelerated Sparse Linear Regression via Random Projection Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He

AAAI 2016 Fast and Accurate Refined Nyström-Based Kernel SVM Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin

ICML 2016 Online Stochastic Linear Optimization Under One-Bit Feedback Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-hua Zhou

UAI 2016 Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang

ALT 2016 Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

AAAI 2016 Stochastic Optimization for Kernel PCA Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

ICML 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi

AISTATS 2015 A Simple Homotopy Algorithm for Compressive Sensing Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

IJCAI 2015 A Simple Probabilistic Extension of Modal Mu-Calculus Wanwei Liu, Lei Song, Ji Wang, Lijun Zhang

ICML 2015 An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu

MLJ 2015 Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD) Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu

COLT 2015 Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization Mehrdad Mahdavi, Lijun Zhang, Rong Jin

AAAI 2015 Online Bandit Learning for a Special Class of Non-Convex Losses Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

IJCAI 2015 Planning for Stochastic Games with Co-Safe Objectives Lei Song, Yuan Feng, Lijun Zhang

AAAI 2015 Preference Planning for Markov Decision Processes Meilun Li, Zhikun She, Andrea Turrini, Lijun Zhang

ICML 2015 Theory of Dual-Sparse Regularized Randomized Reduction Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu

ICML 2014 A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-Dimensional Data Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain

ICML 2014 Efficient Algorithms for Robust One-Bit Compressive Sensing Lijun Zhang, Jinfeng Yi, Rong Jin

AAAI 2014 Sparse Learning for Stochastic Composite Optimization Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He

NeurIPS 2013 Linear Convergence with Condition Number Independent Access of Full Gradients Lijun Zhang, Mehrdad Mahdavi, Rong Jin

NeurIPS 2013 Mixed Optimization for Smooth Functions Mehrdad Mahdavi, Lijun Zhang, Rong Jin

ICML 2013 O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He

ICML 2013 Online Kernel Learning with a near Optimal Sparsity Bound Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He

COLT 2013 Recovering the Optimal Solution by Dual Random Projection Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu

ICML 2013 Semi-Supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil Jain

AAAI 2012 Document Summarization Based on Data Reconstruction Zhanying He, Chun Chen, Jiajun Bu, Can Wang, Lijun Zhang, Deng Cai, Xiaofei He

AAAI 2012 Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression Lijun Zhang, Rong Jin, Chun Chen, Jiajun Bu, Xiaofei He

ICML 2012 Multiple Kernel Learning from Noisy Labels by Stochastic Programming Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou

AAAI 2010 G-Optimal Design with Laplacian Regularization Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, Lijun Zhang, Cheng Zhang

AAAI 2010 Modeling Dynamic Multi-Topic Discussions in Online Forums Hao Wu, Jiajun Bu, Chun Chen, Can Wang, Guang Qiu, Lijun Zhang, Jianfeng Shen