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

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

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

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

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

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

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

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

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

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

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