Dongruo Zhou

发表

Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks

Yuan Cao, Quanquan Gu, Difan Zou, 2018, ArXiv.

Stochastic Nested Variance Reduction for Nonconvex Optimization

Quanquan Gu, Pan Xu, Dongruo Zhou, 2018, J. Mach. Learn. Res..

Finding Local Minima via Stochastic Nested Variance Reduction pdf

Quanquan Gu, Pan Xu, Dongruo Zhou, 2018, ArXiv.

Stochastic Nested Variance-Reduced Gradient Method for Nonconvex Optimization

Dongruo Zhou, 2018 .

NeuralUCB: Contextual Bandits with Neural Network-Based Exploration

Quanquan Gu, Lihong Li, Dongruo Zhou, 2019 .

Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks

Jinghui Chen, Yuan Cao, Quanquan Gu, 2020, IJCAI.

Training Deep Neural Networks with Partially Adaptive Momentum

Jinghui Chen, Yuan Cao, Quanquan Gu, 2019 .

Stochastic Variance-Reduced Cubic Regularized Newton Method

Quanquan Gu, Dongruo Zhou, Pan Xu, 2018, ICML.

Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

Quanquan Gu, Dongruo Zhou, Yue Wu, 2021, AISTATS.

Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation pdf

Quanquan Gu, Dongruo Zhou, Zixiang Chen, 2021, ArXiv.

Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization

Yuan Cao, Quanquan Gu, Dongruo Zhou, 2020, AISTATS.

Lower Bounds for Smooth Nonconvex Finite-Sum Optimization pdf

Quanquan Gu, Dongruo Zhou, Quanquan Gu, 2019, ICML.

Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes pdf

Quanquan Gu, Dongruo Zhou, Csaba Szepesvari, 2020, COLT.

Logarithmic Regret for Reinforcement Learning with Linear Function Approximation pdf

Quanquan Gu, Dongruo Zhou, Jiafan He, 2020, ICML.

Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping pdf

Quanquan Gu, Dongruo Zhou, Jiafan He, 2020, ICML.

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization pdf

Yuan Cao, Quanquan Gu, Dongruo Zhou, 2018, ArXiv.

Neural Contextual Bandits with UCB-based Exploration

Quanquan Gu, Lihong Li, Dongruo Zhou, 2019, ICML.

Neural Contextual Bandits with Upper Confidence Bound-Based Exploration pdf

Quanquan Gu, Lihong Li, Dongruo Zhou, 2019, ArXiv.

Provable Multi-Objective Reinforcement Learning with Generative Models pdf

Jiahao Chen, Quanquan Gu, Dongruo Zhou, 2020, ArXiv.

Stochastic Variance-Reduced Cubic Regularization Methods

Quanquan Gu, Dongruo Zhou, Pan Xu, 2019, J. Mach. Learn. Res..

Stochastic Recursive Variance-Reduced Cubic Regularization Methods pdf

Quanquan Gu, Dongruo Zhou, Quanquan Gu, 2019, AISTATS.

Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization

Quanquan Gu, Pan Xu, Dongruo Zhou, 2018, NeurIPS.

Batched Neural Bandits pdf

Amin Karbasi, Vahab Mirrokni, Khashayar Khosravi, 2021, ArXiv.

Neural Thompson Sampling pdf

Quanquan Gu, Dongruo Zhou, Lihong Li, 2020, ICLR.

Nearly Optimal Regret for Learning Adversarial MDPs with Linear Function Approximation pdf

Quanquan Gu, Dongruo Zhou, Jiafan He, 2021, ArXiv.

Minimax Optimal Reinforcement Learning for Discounted MDPs pdf

Quanquan Gu, Dongruo Zhou, Jiafan He, 2020, ArXiv.

Sample Efficient Stochastic Variance-Reduced Cubic Regularization Method pdf

Quanquan Gu, Pan Xu, Dongruo Zhou, 2018, ArXiv.

Neural Contextual Bandits with UCB-based Exploration

Lihong Li, Quanquan Gu, Dongruo Zhou, 2019, ICML.

Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

Quanquan Gu, Dongruo Zhou, Yue Wu, 2021, AISTATS.

Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping

Quanquan Gu, Dongruo Zhou, Jiafan He, 2020, ICML.