User Modeling for Recommendation in Blogspace. - Kangmiao Liu; Wei Chen 005; Jiajun Bu; Chun Chen 001; Lijun Zhang 005 (Web Intelligence/IAT Workshops, 2007)

Pervasive Web News Recommendation for Visually Impaired People. - Wei Chen 005; Lijun Zhang 005; Can Wang 001; Chun Chen 001; Jiajun Bu (Web Intelligence/IAT Workshops, 2008)

Convex experimental design using manifold structure for image retrieval. - Lijun Zhang 005; Chun Chen 001; Wei Chen 005; Jiajun Bu; Deng Cai 001; Xiaofei He 001 (ACM Multimedia, 2009)

G-Optimal Design with Laplacian Regularization. - Chun Chen 001; Zhengguang Chen; Jiajun Bu; Can Wang 001; Lijun Zhang 005; Cheng Zhang (AAAI, 2010)

Modeling Dynamic Multi-Topic Discussions in Online Forums. - Hao Wu; Jiajun Bu; Chun Chen 001; Can Wang 001; Guang Qiu; Lijun Zhang 005; Jianfeng Shen (AAAI, 2010)

A Metric for Measuring Members' Contribution to Information Propagation in Social Network Sites. - Jiajia Zheng; Wei Chen 005; Lijun Zhang 005; Jiajun Bu; Chun Chen 001 (APWeb, 2010)

Music recommendation by unified hypergraph: combining social media information and music content. - Jiajun Bu; Shulong Tan; Chun Chen 001; Can Wang 001; Hao Wu; Lijun Zhang 005; Xiaofei He 001 (ACM Multimedia, 2010)

Discriminative codeword selection for image representation. - Lijun Zhang 005; Chun Chen 001; Jiajun Bu; Zhengguang Chen; Shulong Tan; Xiaofei He 001 (ACM Multimedia, 2010)

Topic Decomposition and Summarization. - Wei Chen 005; Can Wang 001; Chun Chen 001; Lijun Zhang 005; Jiajun Bu (PAKDD (1), 2010)

Constrained Laplacian Eigenmap for dimensionality reduction. - Chun Chen 001; Lijun Zhang 005; Jiajun Bu; Can Wang 001; Wei Chen 005 (Neurocomputing, 2010)

Online detection of bursty events and their evolution in news streams. - Wei Chen 005; Chun Chen 001; Lijun Zhang 005; Can Wang 001; Jiajun Bu (J. Zhejiang Univ. Sci. C, 2010)

Word line boost and read SA PMOS compensation (SAPC) for ROM in 55nm CMOS. - Ruifeng Huang; Jianbin Zheng; Lijun Zhang 005; Zhaoyong Zhang; Hao Wu; Yue Yu (ASICON, 2011)

Active Learning Based on Locally Linear Reconstruction. - Lijun Zhang 005; Chun Chen 001; Jiajun Bu; Deng Cai 001; Xiaofei He 001; Thomas S. Huang (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Graph Regularized Sparse Coding for Image Representation. - Miao Zheng; Jiajun Bu; Chun Chen 001; Can Wang 001; Lijun Zhang 005; Guang Qiu; Deng Cai 001 (IEEE Trans. Image Process., 2011)

Document Summarization Based on Data Reconstruction. - Zhanying He; Chun Chen 001; Jiajun Bu; Can Wang 001; Lijun Zhang 005; Deng Cai 001; Xiaofei He 001 (AAAI, 2012)

Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression. - Lijun Zhang 005; Rong Jin 001; Chun Chen 001; Jiajun Bu; Xiaofei He 001 (AAAI, 2012)

Multiple Kernel Learning from Noisy Labels by Stochastic Programming. - Tianbao Yang; Mehrdad Mahdavi; Rong Jin 001; Lijun Zhang 005; Yang Zhou 033 (ICML, 2012)

Recovering Optimal Solution by Dual Random Projection - Lijun Zhang 005; Mehrdad Mahdavi; Rong Jin 001; Tianbao Yang (CoRR, 2012)

Locally discriminative topic modeling. - Hao Wu; Jiajun Bu; Chun Chen 001; Jianke Zhu; Lijun Zhang 005; Haifeng Liu 001; Can Wang 001; Deng Cai 001 (Pattern Recognit., 2012)

A Unified Feature and Instance Selection Framework Using Optimum Experimental Design. - Lijun Zhang 005; Chun Chen 001; Jiajun Bu; Xiaofei He 001 (IEEE Trans. Image Process., 2012)

Locally Discriminative Coclustering. - Lijun Zhang 005; Chun Chen 001; Jiajun Bu; Zhengguang Chen; Deng Cai 001; Jiawei Han 001 (IEEE Trans. Knowl. Data Eng., 2012)

Recovering the Optimal Solution by Dual Random Projection. - Lijun Zhang 005; Mehrdad Mahdavi; Rong Jin 001; Tianbao Yang; Shenghuo Zhu (COLT, 2013)

Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. - Jinfeng Yi; Lijun Zhang 005; Rong Jin 001; Qi Qian 001; Anil K. Jain 001 (ICML (3), 2013)

O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Xiaofei He 001 (ICML (3), 2013)

Online Kernel Learning with a Near Optimal Sparsity Bound. - Lijun Zhang 005; Jinfeng Yi; Rong Jin 001; Ming Lin 002; Xiaofei He 001 (ICML (3), 2013)

Linear Convergence with Condition Number Independent Access of Full Gradients. - Lijun Zhang 005; Mehrdad Mahdavi; Rong Jin 001 (NIPS, 2013)

Mixed Optimization for Smooth Functions. - Mehrdad Mahdavi; Lijun Zhang 005; Rong Jin 001 (NIPS, 2013)

Improving the Minimax Rate of Active Learning. - Lijun Zhang 005; Mehrdad Mahdavi; Rong Jin 001 (CoRR, 2013)

Efficient Stochastic Gradient Descent for Strongly Convex Optimization - Tianbao Yang; Lijun Zhang 005 (CoRR, 2013)

Sparse Learning for Stochastic Composite Optimization. - Weizhong Zhang; Lijun Zhang 005; Yao Hu; Rong Jin 001; Deng Cai 001; Xiaofei He 001 (AAAI, 2014)

Efficient Algorithms for Robust One-bit Compressive Sensing. - Lijun Zhang 005; Jinfeng Yi; Rong Jin 001 (ICML, 2014)

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data. - Jinfeng Yi; Lijun Zhang 005; Jun Wang 006; Rong Jin 001; Anil K. Jain 001 (ICML, 2014)

Binary Excess Risk for Smooth Convex Surrogates. - Mehrdad Mahdavi; Lijun Zhang 005; Rong Jin 001 (CoRR, 2014)

A Simple Homotopy Proximal Mapping for Compressive Sensing. - Tianbao Yang; Lijun Zhang 005; Rong Jin 001; Shenghuo Zhu (CoRR, 2014)

Random Projections for Classification: A Recovery Approach. - Lijun Zhang 005; Mehrdad Mahdavi; Rong Jin 001; Tianbao Yang; Shenghuo Zhu (IEEE Trans. Inf. Theory, 2014)

Online Bandit Learning for a Special Class of Non-Convex Losses. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (AAAI, 2015)

A Simple Homotopy Algorithm for Compressive Sensing. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (AISTATS, 2015)

Design and implementation of precise measuring method for the access time of embedded memory. - Yuqing Hu; Lijun Zhang 005; Youzhong Li; Qixiao Zhang; Erliang Li; Wei Jiang 029 (ASICON, 2015)

Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. - Mehrdad Mahdavi; Lijun Zhang 005; Rong Jin 001 (COLT, 2015)

An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection. - Tianbao Yang; Lijun Zhang 005; Rong Jin 001; Shenghuo Zhu (ICML, 2015)

Theory of Dual-sparse Regularized Randomized Reduction. - Tianbao Yang; Lijun Zhang 005; Rong Jin 001; Shenghuo Zhu (ICML, 2015)

An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints. - Jinfeng Yi; Lijun Zhang 005; Tianbao Yang; Wei Liu 005; Jun Wang 006 (KDD, 2015)

Analysis of Nuclear Norm Regularization for Full-rank Matrix Completion. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (CoRR, 2015)

Online Stochastic Linear Optimization under One-bit Feedback. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (CoRR, 2015)

Stochastic Proximal Gradient Descent for Nuclear Norm Regularization. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (CoRR, 2015)

Towards Making High Dimensional Distance Metric Learning Practical. - Qi Qian 001; Rong Jin 001; Lijun Zhang 005; Shenghuo Zhu (CoRR, 2015)

Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees. - Tianbao Yang; Lijun Zhang 005; Qihang Lin; Rong Jin 001 (CoRR, 2015)

Unsupervised document summarization from data reconstruction perspective. - Zhanying He; Chun Chen 001; Jiajun Bu; Can Wang 001; Lijun Zhang 005; Deng Cai 001; Xiaofei He 001 (Neurocomputing, 2015)

Graph-based local concept coordinate factorization. - Ping Li 006; Jiajun Bu; Lijun Zhang 005; Chun Chen 001 (Knowl. Inf. Syst., 2015)

Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). - Qi Qian 001; Rong Jin 001; Jinfeng Yi; Lijun Zhang 005; Shenghuo Zhu (Mach. Learn., 2015)

Multi-View Concept Learning for Data Representation. - Ziyu Guan; Lijun Zhang 005; Jinye Peng; Jianping Fan 001 (IEEE Trans. Knowl. Data Eng., 2015)

Expert Finding for Question Answering via Graph Regularized Matrix Completion. - Zhou Zhao 001; Lijun Zhang 005; Xiaofei He 001; Wilfred Ng (IEEE Trans. Knowl. Data Eng., 2015)

Stochastic Optimization for Kernel PCA. - Lijun Zhang 005; Tianbao Yang; Jinfeng Yi; Rong Jin 001; Zhi-Hua Zhou (AAAI, 2016)

Fast and Accurate Refined Nyström-Based Kernel SVM. - Zhe Li 008; Tianbao Yang; Lijun Zhang 005; Rong Jin 001 (AAAI, 2016)

Accelerated Sparse Linear Regression via Random Projection. - Weizhong Zhang; Lijun Zhang 005; Rong Jin 001; Deng Cai 001; Xiaofei He 001 (AAAI, 2016)

Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (ALT, 2016)

Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. - Tianbao Yang; Lijun Zhang 005; Rong Jin 001; Jinfeng Yi (ICML, 2016)

Online Stochastic Linear Optimization under One-bit Feedback. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Yichi Xiao; Zhi-Hua Zhou (ICML, 2016)

Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. - Jianhui Chen; Tianbao Yang; Qihang Lin; Lijun Zhang 005; Yi Chang 001 (UAI, 2016)

Improved dynamic regret for non-degeneracy functions. - Lijun Zhang 005; Tianbao Yang; Jinfeng Yi; Rong Jin 001; Zhi-Hua Zhou (CoRR, 2016)

Online kernel learning with nearly constant support vectors. - Ming Lin 002; Lijun Zhang 005; Rong Jin 001; Shifeng Weng; Changshui Zhang (Neurocomputing, 2016)

A-Optimal Projection for Image Representation. - Xiaofei He 001; Chiyuan Zhang; Lijun Zhang 005; Xuelong Li 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Graph Regularized Feature Selection with Data Reconstruction. - Zhou Zhao 001; Xiaofei He 001; Deng Cai 001; Lijun Zhang 005; Wilfred Ng; Yueting Zhuang (IEEE Trans. Knowl. Data Eng., 2016)

A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis. - Zhe Li 008; Tianbao Yang; Lijun Zhang 005; Rong Jin 001 (AAAI, 2017)

Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee. - Yi Xu 008; Haiqin Yang; Lijun Zhang 005; Tianbao Yang (AAAI, 2017)

Efficient Stochastic Optimization for Low-Rank Distance Metric Learning. - Jie Zhang; Lijun Zhang 005 (AAAI, 2017)

Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001 (COLT, 2017)

A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates. - Tianbao Yang; Qihang Lin; Lijun Zhang 005 (ICML, 2017)

Illumination Quality Assessment for Face Images: A Benchmark and a Convolutional Neural Networks Based Model. - Lijun Zhang 005; Lin Zhang 014; Lida Li (ICONIP (3), 2017)

Storage Fit Learning with Unlabeled Data. - Bo-Jian Hou; Lijun Zhang 005; Zhi-Hua Zhou (IJCAI, 2017)

SVD-free Convex-Concave Approaches for Nuclear Norm Regularization. - Yichi Xiao; Zhe Li 008; Tianbao Yang; Lijun Zhang 005 (IJCAI, 2017)

Semi-Supervised Deep Hashing with a Bipartite Graph. - Xinyu Yan; Lijun Zhang 005; Wu-Jun Li (IJCAI, 2017)

Improved Dynamic Regret for Non-degenerate Functions. - Lijun Zhang 005; Tianbao Yang; Jinfeng Yi; Rong Jin 001; Zhi-Hua Zhou (NIPS, 2017)

Scalable Demand-Aware Recommendation. - Jinfeng Yi; Cho-Jui Hsieh; Kush R. Varshney; Lijun Zhang 005; Yao Li 015 (NIPS, 2017)

Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n2)-type of Risk Bounds. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001 (CoRR, 2017)

Strongly Adaptive Regret Implies Optimally Dynamic Regret. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (CoRR, 2017)

Positive-Unlabeled Demand-Aware Recommendation. - Jinfeng Yi; Cho-Jui Hsieh; Kush R. Varshney; Lijun Zhang 005; Yao Li 015 (CoRR, 2017)

Non-redundant multiple clustering by nonnegative matrix factorization. - Sen Yang; Lijun Zhang 005 (Mach. Learn., 2017)

Sparse Learning with Stochastic Composite Optimization. - Weizhong Zhang; Lijun Zhang 005; Zhongming Jin 001; Rong Jin 001; Deng Cai 001; Xuelong Li 001; Ronghua Liang; Xiaofei He 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer. - Tianbao Yang; Zhe Li 008; Lijun Zhang 005 (AISTATS, 2018)

Query-Efficient Black-Box Attack by Active Learning. - Pengcheng Li; Jinfeng Yi; Lijun Zhang 005 (ICDM, 2018)

Image Exposure Assessment: A Benchmark and a Deep Convolutional Neural Networks Based Model. - Lijun Zhang 005; Lin Zhang 014; Xiao Liu 030; Ying Shen 005; Dongqing Wang (ICME, 2018)

Dynamic Regret of Strongly Adaptive Methods. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (ICML, 2018)

Efficient Adaptive Online Learning via Frequent Directions. - Yuanyu Wan; Nan Wei; Lijun Zhang 005 (IJCAI, 2018)

Minimizing Adaptive Regret with One Gradient per Iteration. - Guanghui Wang 006; Dakuan Zhao; Lijun Zhang 005 (IJCAI, 2018)

Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. - Mingrui Liu; Xiaoxuan Zhang; Lijun Zhang 005; Rong Jin 001; Tianbao Yang (NeurIPS, 2018)

Adaptive Online Learning in Dynamic Environments. - Lijun Zhang 005; Shiyin Lu; Zhi-Hua Zhou (NeurIPS, 2018)

ell_1-regression with Heavy-tailed Distributions. - Lijun Zhang 005; Zhi-Hua Zhou (NeurIPS, 2018)

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. - Fanhua Shang; Kaiwen Zhou; James Cheng; Ivor W. Tsang; Lijun Zhang 005; Dacheng Tao (CoRR, 2018)

𝓁1-regression with Heavy-tailed Distributions. - Lijun Zhang 005; Zhi-Hua Zhou (CoRR, 2018)

Matrix Completion from Non-Uniformly Sampled Entries. - Yuanyu Wan; Jinfeng Yi; Lijun Zhang 005 (CoRR, 2018)

Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate. - Lijun Zhang 005; Zhi-Hua Zhou (COLT, 2019)

Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards. - Shiyin Lu; Guanghui Wang 006; Yao Hu; Lijun Zhang 005 (ICML, 2019)

Adaptive Regret of Convex and Smooth Functions. - Lijun Zhang 005; Tie-Yan Liu; Zhi-Hua Zhou (ICML, 2019)

Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss. - Pengcheng Li; Jinfeng Yi; Bowen Zhou 001; Lijun Zhang 005 (IJCAI, 2019)

Multi-Objective Generalized Linear Bandits. - Shiyin Lu; Guanghui Wang 006; Yao Hu; Lijun Zhang 005 (IJCAI, 2019)

Generative Adversarial Network-based Image Super-Resolution with a Novel Quality Loss. - Xining Zhu; Lin Zhang 014; Lijun Zhang 005; Xiao Liu 030; Ying Shen 005; Shengjie Zhao 001 (ISPACS, 2019)

Zero-Shot Restoration of Back-lit Images Using Deep Internal Learning. - Lin Zhang 014; Lijun Zhang 005; Xiao Liu 030; Ying Shen 005; Shaoming Zhang; Shengjie Zhao 001 (ACM Multimedia, 2019)

Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization. - Guanghui Wang 006; Shiyin Lu; Lijun Zhang 005 (UAI, 2019)

Stochastic Primal-Dual Algorithms with Faster Convergence than O(1/√T) for Problems without Bilinear Structure. - Yan Yan 006; Yi Xu 008; Qihang Lin; Lijun Zhang 005; Tianbao Yang (CoRR, 2019)

SAdam: A Variant of Adam for Strongly Convex Functions. - Guanghui Wang 006; Shiyin Lu; Weiwei Tu; Lijun Zhang 005 (CoRR, 2019)

Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. - Lijun Zhang 005; Guanghui Wang 006; Weiwei Tu; Zhi-Hua Zhou (CoRR, 2019)

More Adaptive Algorithms for Tracking the Best Expert. - Shiyin Lu; Lijun Zhang 005 (CoRR, 2019)

Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion. - Lijun Zhang 005; Tianbao Yang; Rong Jin 001; Zhi-Hua Zhou (J. Mach. Learn. Res., 2019)

A simple homotopy proximal mapping algorithm for compressive sensing. - Tianbao Yang; Lijun Zhang 005; Rong Jin 001; Shenghuo Zhu; Zhi-Hua Zhou (Mach. Learn., 2019)

Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization. - Guanghui Wang 006; Shiyin Lu; Yao Hu; Lijun Zhang 005 (AAAI, 2020)

Minimizing Dynamic Regret and Adaptive Regret Simultaneously. - Lijun Zhang 005; Shiyin Lu; Tianbao Yang (AISTATS, 2020)

A Simple Approach for Non-stationary Linear Bandits. - Peng Zhao 006; Lijun Zhang 005; Yuan Jiang 001; Zhi-Hua Zhou (AISTATS, 2020)

Improving Multi-Scenario Learning to Rank in E-commerce by Exploiting Task Relationships in the Label Space. - Pengcheng Li; Runze Li; Qing Da; Anxiang Zeng; Lijun Zhang 005 (CIKM, 2020)

SAdam: A Variant of Adam for Strongly Convex Functions. - Guanghui Wang 006; Shiyin Lu; Quan Cheng 001; Weiwei Tu; Lijun Zhang 005 (ICLR, 2020)

Stochastic Optimization for Non-convex Inf-Projection Problems. - Yan Yan 006; Yi Xu 008; Lijun Zhang 005; Xiaoyu Wang 002; Tianbao Yang (ICML, 2020)

Projection-free Distributed Online Convex Optimization with $O( sqrt{T})$ Communication Complexity. - Yuanyu Wan; Wei-Wei Tu; Lijun Zhang 005 (ICML, 2020)

Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. - Bo Xue 004; Guanghui Wang 006; Yimu Wang; Lijun Zhang 005 (IJCAI, 2020)

Online Learning in Changing Environments. - Lijun Zhang 005 (IJCAI, 2020)

Searching Privately by Imperceptible Lying: A Novel Private Hashing Method with Differential Privacy. - Yimu Wang; Shiyin Lu; Lijun Zhang 005 (ACM Multimedia, 2020)

Dynamic Regret of Convex and Smooth Functions. - Peng Zhao 006; Yu-Jie Zhang; Lijun Zhang 005; Zhi-Hua Zhou (NeurIPS, 2020)

Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search. - Yimu Wang; Xiu-Shen Wei; Bo Xue 004; Lijun Zhang 005 (PRCV (2), 2020)

An Adversarial Domain Adaptation Network For Cross-Domain Fine-Grained Recognition. - Yimu Wang; Ren-Jie Song; Xiu-Shen Wei; Lijun Zhang 005 (WACV, 2020)

SID-NISM: A Self-supervised Low-light Image Enhancement Framework. - Lijun Zhang 005; Xiao Liu 030; Erik G. Learned-Miller; Hui Guan 001 (CoRR, 2020)

Accelerating adaptive online learning by matrix approximation. - Yuanyu Wan; Lijun Zhang 005 (Int. J. Data Sci. Anal., 2020)

High-dimensional model recovery from random sketched data by exploring intrinsic sparsity. - Tianbao Yang; Lijun Zhang 005; Qihang Lin; Shenghuo Zhu; Rong Jin 001 (Mach. Learn., 2020)

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. - Fanhua Shang; Kaiwen Zhou; Hongying Liu 001; James Cheng; Ivor W. Tsang; Lijun Zhang 005; Dacheng Tao; Licheng Jiao (IEEE Trans. Knowl. Data Eng., 2020)

Stochastic Bandits with Graph Feedback in Non-Stationary Environments. - Shiyin Lu; Yao Hu; Lijun Zhang 005 (AAAI, 2021)

Stochastic Graphical Bandits with Adversarial Corruptions. - Shiyin Lu; Guanghui Wang 006; Lijun Zhang 005 (AAAI, 2021)

Projection-free Online Learning in Dynamic Environments. - Yuanyu Wan; Bo Xue 004; Lijun Zhang 005 (AAAI, 2021)

Approximate Multiplication of Sparse Matrices with Limited Space. - Yuanyu Wan; Lijun Zhang 005 (AAAI, 2021)

Projection-free Online Learning over Strongly Convex Sets. - Yuanyu Wan; Lijun Zhang 005 (AAAI, 2021)

Learning to Augment Imbalanced Data for Re-ranking Models. - Zi-Hao Qiu; Ying-Chun Jian; Qing-Guo Chen; Lijun Zhang 005 (CIKM, 2021)

Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. - Hui Guan 001; Umana Chaudhary; Yuanchao Xu 001; Lin Ning 001; Lijun Zhang 005; Xipeng Shen (ICDM, 2021)

Deep Unified Cross-Modality Hashing by Pairwise Data Alignment. - Yimu Wang; Bo Xue 004; Quan Cheng 001; Yuhui Chen; Lijun Zhang 005 (IJCAI, 2021)

Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. - Peng Zhao 006; Lijun Zhang 005 (L4DC, 2021)

Online Convex Optimization with Continuous Switching Constraint. - Guanghui Wang 006; Yuanyu Wan; Tianbao Yang; Lijun Zhang 005 (NeurIPS, 2021)

Revisiting Smoothed Online Learning. - Lijun Zhang 005; Wei Jiang 029; Shiyin Lu; Tianbao Yang (NeurIPS, 2021)

Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. - Lijun Zhang 005; Guanghui Wang 006; Wei-Wei Tu; Wei Jiang 029; Zhi-Hua Zhou (NeurIPS, 2021)

Non-stationary Linear Bandits Revisited. - Peng Zhao 006; Lijun Zhang 005 (CoRR, 2021)

Projection-free Distributed Online Learning with Strongly Convex Losses. - Yuanyu Wan; Guanghui Wang 006; Lijun Zhang 005 (CoRR, 2021)

Rethinking Hard-Parameter Sharing in Multi-Task Learning. - Lijun Zhang 005; Qizheng Yang; Xiao Liu 030; Hui Guan 001 (CoRR, 2021)

AutoMTL: A Programming Framework for Automated Multi-Task Learning. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (CoRR, 2021)

Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression. - Yuezhou Sun; Wenlong Zhao 001; Lijun Zhang 005; Xiao Liu 030; Hui Guan 001; Matei Zaharia (CoRR, 2021)

Reuse-centric k-means configuration. - Lijun Zhang 005; Hui Guan 001; Yufei Ding 001; Xipeng Shen; Hamid Krim (Inf. Syst., 2021)

Bandit Convex Optimization in Non-stationary Environments. - Peng Zhao 006; Guanghui Wang 006; Lijun Zhang 005; Zhi-Hua Zhou (J. Mach. Learn. Res., 2021)

Learning With Feature Evolvable Streams. - Bo-Jian Hou; Lijun Zhang 005; Zhi-Hua Zhou (IEEE Trans. Knowl. Data Eng., 2021)

Charging Task Scheduling for Directional Wireless Charger Networks. - Haipeng Dai 001; Ke Sun 012; Alex X. Liu; Lijun Zhang 005; Jiaqi Zheng 001; Guihai Chen (IEEE Trans. Mob. Comput., 2021)

Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. - Guanghui Wang 006; Ming Yang; Lijun Zhang 005; Tianbao Yang (AISTATS, 2022)

A Tree-Structured Multi-Task Model Recommender. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (AutoML, 2022)

Rethinking Hard-Parameter Sharing in Multi-Domain Learning. - Lijun Zhang 005; Qizheng Yang; Xiao Liu 030; Hui Guan 001 (ICME, 2022)

Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. - Wei Jiang 029; Bokun Wang; Yibo Wang 005; Lijun Zhang 005; Tianbao Yang (ICML, 2022)

Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence. - Zi-Hao Qiu; Quanqi Hu; Yongjian Zhong; Lijun Zhang 005; Tianbao Yang (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 005; Denny Zhou; Tianbao Yang (ICML, 2022)

A Simple yet Universal Strategy for Online Convex Optimization. - Lijun Zhang 005; Guanghui Wang 006; Jinfeng Yi; Tianbao Yang (ICML, 2022)

Efficient Methods for Non-stationary Online Learning. - Peng Zhao 006; Yan-Feng Xie; Lijun Zhang 005; Zhi-Hua Zhou (NeurIPS, 2022)

Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. - Wei Jiang 029; Gang Li; Yibo Wang 005; Lijun Zhang 005; Tianbao Yang (NeurIPS, 2022)

Online Frank-Wolfe with Arbitrary Delays. - Yuanyu Wan; Wei-Wei Tu; Lijun Zhang 005 (NeurIPS, 2022)

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. - Lijun Zhang 005; Wei Jiang 029; Jinfeng Yi; Tianbao Yang (NeurIPS, 2022)

AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (NeurIPS, 2022)

Adaptive Feature Generation for Online Continual Learning from Imbalanced Data. - Yingchun Jian; Jinfeng Yi; Lijun Zhang 005 (PAKDD (1), 2022)

Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization. - Shiyin Lu; Yu-Hang Zhou; Jing-Cheng Shi; Wenya Zhu; Qingtao Yu; Qing-Guo Chen; Qing Da; Lijun Zhang 005 (WSDM, 2022)

Strongly adaptive online learning over partial intervals. - Yuanyu Wan; Wei-Wei Tu; Lijun Zhang 005 (Sci. China Inf. Sci., 2022)

Online Frank-Wolfe with Unknown Delays. - Yuanyu Wan; Wei-Wei Tu; Lijun Zhang 005 (CoRR, 2022)

Break the Wall Between Homophily and Heterophily for Graph Representation Learning. - Xiao Liu 030; Lijun Zhang 005; Hui Guan 001 (CoRR, 2022)

Projection-free Distributed Online Learning with Sublinear Communication Complexity. - Yuanyu Wan; Guanghui Wang 006; Wei-Wei Tu; Lijun Zhang 005 (J. Mach. Learn. Res., 2022)

Online strongly convex optimization with unknown delays. - Yuanyu Wan; Wei-Wei Tu; Lijun Zhang 005 (Mach. Learn., 2022)

Efficient Adaptive Online Learning via Frequent Directions. - Yuanyu Wan; Lijun Zhang 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Prediction With Unpredictable Feature Evolution. - Bo-Jian Hou; Lijun Zhang 005; Zhi-Hua Zhou (IEEE Trans. Neural Networks Learn. Syst., 2022)

Distributed Projection-Free Online Learning for Smooth and Convex Losses. - Yibo Wang 005; Yuanyu Wan; Shimao Zhang; Lijun Zhang 005 (AAAI, 2023)

Improved Dynamic Regret for Online Frank-Wolfe. - Yuanyu Wan; Lijun Zhang 005; Mingli Song (COLT, 2023)

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. - Sijia Chen; Wei-Wei Tu; Peng Zhao 006; Lijun Zhang 005 (ICML, 2023)

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. - Quanqi Hu; Zi-Hao Qiu; Zhishuai Guo; Lijun Zhang 005; Tianbao Yang (ICML, 2023)

Learning Unnormalized Statistical Models via Compositional Optimization. - Wei Jiang 029; Jiayu Qin 001; Lingyu Wu; Changyou Chen; Tianbao Yang; Lijun Zhang 005 (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 005; Tianbao Yang (ICML, 2023)

Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. - Bo Xue 004; Yimu Wang; Yuanyu Wan; Jinfeng Yi; Lijun Zhang 005 (NeurIPS, 2023)

Stochastic Approximation Approaches to Group Distributionally Robust Optimization. - Lijun Zhang 005; Peng Zhao 006; Zhen-Hua Zhuang; Tianbao Yang; Zhi-Hua Zhou (NeurIPS, 2023)

Flow: Per-instance Personalized Federated Learning. - Kunjal Panchal; Sunav Choudhary; Nisarg Parikh; Lijun Zhang 005; Hui Guan 001 (NeurIPS, 2023)

Stochastic Graphical Bandits with Heavy-Tailed Rewards. - Yutian Gou; Jinfeng Yi; Lijun Zhang 005 (UAI, 2023)

An Alternative Hard-Parameter Sharing Paradigm for Multi-Domain Learning. - Lijun Zhang 005; Qizheng Yang; Xiao Liu 030; Hui Guan 001 (IEEE Access, 2023)

Stochastic Approximation Approaches to Group Distributionally Robust Optimization. - Lijun Zhang 005; Peng Zhao 006; Tianbao Yang; Zhi-Hua Zhou (CoRR, 2023)

Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. - Lijun Zhang 005; Xiao Liu 030; Kaleel Mahmood; Caiwen Ding; Hui Guan 001 (CoRR, 2023)

Efficient Stochastic Approximation of Minimax Excess Risk Optimization. - Lijun Zhang 005; Wei-Wei Tu (CoRR, 2023)

Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees. - Yibo Wang 005; Wenhao Yang; Wei Jiang 029; Shiyin Lu; Bing Wang 017; Haihong Tang; Yuanyu Wan; Lijun Zhang 005 (AAAI, 2024)

Nearly Optimal Regret for Decentralized Online Convex Optimization. - Yuanyu Wan; Tong Wei 001; Mingli Song; Lijun Zhang 005 (COLT, 2024)

GMorph: Accelerating Multi-DNN Inference via Model Fusion. - Qizheng Yang; Tianyi Yang; Mingcan Xiang; Lijun Zhang 005; Haoliang Wang; Marco Serafini; Hui Guan 001 (EuroSys, 2024)

Efficient Stochastic Approximation of Minimax Excess Risk Optimization. - Lijun Zhang 005; Haomin Bai; Wei-Wei Tu; Ping Yang; Yao Hu (ICML, 2024)

Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization. - Wei Jiang 029; Sifan Yang; Wenhao Yang; Yibo Wang 005; Yuanyu Wan; Lijun Zhang 005 (ICML, 2024)

High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails. - Langqi Liu; Yibo Wang 005; Lijun Zhang 005 (ICML, 2024)

To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. - Zi-Hao Qiu; Siqi Guo 003; Mao Xu; Tuo Zhao; Lijun Zhang 005; Tianbao Yang (ICML, 2024)

Non-stationary Online Convex Optimization with Arbitrary Delays. - Yuanyu Wan; Chang Yao; Mingli Song; Lijun Zhang 005 (ICML, 2024)

Small-loss Adaptive Regret for Online Convex Optimization. - Wenhao Yang; Wei Jiang 029; Yibo Wang 005; Ping Yang; Yao Hu; Lijun Zhang 005 (ICML, 2024)

Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond. - Dingzhi Yu; Yunuo Cai; Wei Jiang 029; Lijun Zhang 005 (ICML, 2024)

Structured Pruning for Multi-Task Deep Neural Networks. - Siddhant Garg; Lijun Zhang 005; Hui Guan 001 (MIPR, 2024)

Online Composite Optimization Between Stochastic and Adversarial Environments. - Yibo Wang 005; Sijia Chen; Wei Jiang 029; Wenhao Yang; Yuanyu Wan; Lijun Zhang 005 (NeurIPS, 2024)

Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees. - Sijia Chen; Yibo Wang 005; Yi-Feng Wu; Qingguo Chen; Zhao Xu; Weihua Luo; Kaifu Zhang; Lijun Zhang 005 (NeurIPS, 2024)

Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions. - Wei Jiang 029; Sifan Yang; Yibo Wang 005; Lijun Zhang 005 (NeurIPS, 2024)

Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction. - Wei Jiang 029; Sifan Yang; Wenhao Yang; Lijun Zhang 005 (NeurIPS, 2024)

Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. - Kunjal Panchal; Nisarg Parikh; Sunav Choudhary; Lijun Zhang 005; Yuriy Brun; Hui Guan 001 (NeurIPS, 2024)

Improved Regret for Bandit Convex Optimization with Delayed Feedback. - Yuanyu Wan; Chang Yao; Mingli Song; Lijun Zhang 005 (NeurIPS, 2024)

Universal Online Convex Optimization with 1 Projection per Round. - Wenhao Yang; Yibo Wang 005; Peng Zhao 006; Lijun Zhang 005 (NeurIPS, 2024)

Attack-Resilient Image Watermarking Using Stable Diffusion. - Lijun Zhang 005; Xiao Liu 030; Antoni Viros Martin; Cindy Xiong Bearfield; Yuriy Brun; Hui Guan 001 (NeurIPS, 2024)

Not All Embeddings are Created Equal: Towards Robust Cross-domain Recommendation via Contrastive Learning. - Wenhao Yang; Yingchun Jian; Yibo Wang 005; Shiyin Lu; Lei Shen; Bing Wang 017; Haihong Tang; Lijun Zhang 005 (WWW, 2024)

Information-Enhanced Graph Neural Network for Transcending Homophily Barriers. - Xiao Liu 030; Lijun Zhang 005; Hui Guan 001 (IEEE Access, 2024)

Robust Image Watermarking using Stable Diffusion. - Lijun Zhang 005; Xiao Liu 030; Antoni Viros Martin; Cindy Xiong Bearfield; Yuriy Brun; Hui Guan 001 (CoRR, 2024)

Efficient Algorithms for Empirical Group Distributional Robust Optimization and Beyond. - Dingzhi Yu; Yunuo Cai; Wei Jiang 029; Lijun Zhang 005 (CoRR, 2024)

Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models. - Xiao Liu 030; Lijun Zhang 005; Deepak Ganesan; Hui Guan 001 (CoRR, 2024)

Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. - Peng Zhao 006; Yu-Jie Zhang; Lijun Zhang 005; Zhi-Hua Zhou (J. Mach. Learn. Res., 2024)

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. - Sijia Chen; Yu-Jie Zhang; Wei-Wei Tu; Peng Zhao 006; Lijun Zhang 005 (J. Mach. Learn. Res., 2024)

A Tree-Structured Multitask Model Architectures Recommendation System. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation. - Yibo Wang 005; Yingchun Jian; Wenhao Yang; Shiyin Lu; Lei Shen; Bing Wang 017; Xiaoyi Zeng; Lijun Zhang 005 (AAAI, 2025)

Revisiting Projection-Free Online Learning with Time-Varying Constraints. - Yibo Wang 005; Yuanyu Wan; Lijun Zhang 005 (AAAI, 2025)

PVBF: A framework for mitigating parameter variation imbalance in online continual learning. - Zelin Tao; Hao Deng 002; Mingqing Liu; Lijun Zhang 005; Shengjie Zhao 001 (Neural Networks, 2025)

Optimal large-scale stochastic optimization of NDCG surrogates for deep learning. - Zi-Hao Qiu; Quanqi Hu; Yongjian Zhong; Wei-Wei Tu; Lijun Zhang 005; Tianbao Yang (Mach. Learn., 2025)

Mirror Descent Under Generalized Smoothness. - Dingzhi Yu; Wei Jiang 029; Yuanyu Wan; Lijun Zhang 005 (CoRR, 2025)

PVBF: A Framework for Mitigating Parameter Variation Imbalance in Online Continual Learning. - Ze Tao; Hao Deng 002; Mingqing Liu; Lijun Zhang 005; Shengjie Zhao 001 (CoRR, 2025)

Continuous Subspace Optimization for Continual Learning. - Quan Cheng 001; Yuanyu Wan; Lingyu Wu; Chenping Hou; Lijun Zhang 005 (CoRR, 2025)

Communication-Efficient Multi-Device Inference Acceleration for Transformer Models. - Xiao Liu 030; Lijun Zhang 005; Deepak Ganesan; Hui Guan 001 (CoRR, 2025)

Continual Learning With Unknown Task Boundary. - Xiaoxie Zhu; Jinfeng Yi; Lijun Zhang 005 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Improved Analysis for Sign-based Methods with Momentum Updates. - Wei Jiang 029; Dingzhi Yu; Sifan Yang; Wenhao Yang; Lijun Zhang 005 (CoRR, 2025)

Revisiting Stochastic Multi-Level Compositional Optimization. - Wei Jiang 029; Sifan Yang; Yibo Wang 005; Tianbao Yang; Lijun Zhang 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Dual Adaptivity: Universal Algorithms for Minimizing the Adaptive Regret of Convex Functions. - Lijun Zhang 005; Wenhao Yang; Guanghui Wang 006; Wei Jiang 029; Zhi-Hua Zhou (CoRR, 2025)

Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting. - Sifan Yang; Yuanyu Wan; Lijun Zhang 005 (CoRR, 2025)