Zhe Wang - RankMe

25 papers A* 7A 2Journal 16

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	A Cubic Regularization Approach for Finding Local Minimax Points in Nonconvex Minimax Optimization. Trans. Mach. Learn. Res. Ziyi Chen, Zhengyang Hu, Qunwei Li, Zhe Wang, Yi Zhou
2020	J	`jnl`	Enhanced First and Zeroth Order Variance Reduced Algorithms for Min-Max Optimization. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang, H. Vincent Poor
2020	A*	`conf`	History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms. ICML Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang
2020	A*	`conf`	Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms. NeurIPS Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Improving Sample Complexity Bounds for Actor-Critic Algorithms. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang
2020	A*	`conf`	Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. IJCAI Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
2020	J	`jnl`	Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. CoRR Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
2020	A*	`conf`	Reanalysis of Variance Reduced Temporal Difference Learning. ICLR Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang
2020	J	`jnl`	Reanalysis of Variance Reduced Temporal Difference Learning. CoRR Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang
2020	J	`jnl`	Spectral Algorithms for Community Detection in Directed Networks. CoRR Zhe Wang, Yingbin Liang, Pengsheng Ji
2020	J	`jnl`	Spectral Algorithms for Community Detection in Directed Networks. J. Mach. Learn. Res. Zhe Wang, Yingbin Liang, Pengsheng Ji
2019	J	`jnl`	A note on inexact gradient and Hessian conditions for cubic regularized Newton's method. Oper. Res. Lett. Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2019	A	`conf`	Cubic Regularization with Momentum for Nonconvex Optimization. UAI Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2019	J	`jnl`	Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation. CoRR Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	A*	`conf`	Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. ICML Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	J	`jnl`	Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. CoRR Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	A*	`conf`	SpiderBoost and Momentum: Faster Variance Reduction Algorithms. NeurIPS Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
2019	A	`conf`	Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. AISTATS Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	J	`jnl`	A Note on Inexact Condition for Cubic Regularized Newton's Method. CoRR Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	A*	`conf`	Convergence of Cubic Regularization for Nonconvex Optimization under KL Property. NeurIPS Yi Zhou, Zhe Wang, Yingbin Liang
2018	J	`jnl`	Convergence of Cubic Regularization for Nonconvex Optimization under KL Property. CoRR Yi Zhou, Zhe Wang, Yingbin Liang
2018	J	`jnl`	Cubic Regularization with Momentum for Nonconvex Optimization. CoRR Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	J	`jnl`	Sample Complexity of Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. CoRR Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	J	`jnl`	SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization. CoRR Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh