Zhe Wang

According to our database, Zhe Wang authored at least 18 papers between 2018 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2020

Spectral Algorithms for Community Detection in Directed Networks.

Zhe Wang, Yingbin Liang, Pengsheng Ji

J. Mach. Learn. Res., 2020

Enhanced First and Zeroth Order Variance Reduced Algorithms for Min-Max Optimization.

Tengyu Xu, Zhe Wang, Yingbin Liang, H. Vincent Poor

CoRR, 2020

Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms.

Tengyu Xu, Zhe Wang, Yingbin Liang

CoRR, 2020

Improving Sample Complexity Bounds for Actor-Critic Algorithms.

Tengyu Xu, Zhe Wang, Yingbin Liang

CoRR, 2020

Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms.

Tengyu Xu, Zhe Wang, Yingbin Liang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization.

Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms.

Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang

Proceedings of the 37th International Conference on Machine Learning, 2020

Reanalysis of Variance Reduced Temporal Difference Learning.

Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A note on inexact gradient and Hessian conditions for cubic regularized Newton's method.

Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan

Oper. Res. Lett., 2019

Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation.

Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang

CoRR, 2019

Cubic Regularization with Momentum for Nonconvex Optimization.

Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

SpiderBoost and Momentum: Faster Variance Reduction Algorithms.

Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization.

Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang

Proceedings of the 36th International Conference on Machine Learning, 2019

Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization.

Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization.

Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh

CoRR, 2018

A Note on Inexact Condition for Cubic Regularized Newton's Method.

Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan

CoRR, 2018

Sample Complexity of Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization.

Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan

CoRR, 2018

Convergence of Cubic Regularization for Nonconvex Optimization under KL Property.

Yi Zhou, Zhe Wang, Yingbin Liang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018