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Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning

Oct 15, 2020
Kaiyi Ji, Junjie Yang, Yingbin Liang

* 30 pages, 14 figures, 3 tables 

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Finite-Time Analysis for Double Q-learning

Oct 12, 2020
Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang

* Accepted to NeurIPS 2020. The camera-ready version will include additional updates 

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Spectral Algorithms for Community Detection in Directed Networks

Aug 09, 2020
Zhe Wang, Yingbin Liang, Pengsheng Ji

* Journal of Machine Learning Research 2020, to appear 

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Momentum Q-learning with Finite-Sample Convergence Guarantee

Jul 30, 2020
Bowen Weng, Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang


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Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent

Jul 15, 2020
Bowen Weng, Huaqing Xiong, Yingbin Liang, Wei Zhang

* Proceedings of the Twenty-Ninth International Joint Conference IJCAI20 (2020) 3051-3057 
* This paper extends the work presented at the 2020 International Joint Conferences on Artificial Intelligence with supplementary materials 

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When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence

Jun 25, 2020
Ziwei Guan, Tengyu Xu, Yingbin Liang

* Submitted for publication 

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

Jun 17, 2020
Tengyu Xu, Zhe Wang, Yingbin Liang, H. Vincent Poor

* 43 pages, 6 figures 

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Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters

Jun 16, 2020
Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor

* 28 pages, 8 figures, 2 tables 

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

May 08, 2020
Tengyu Xu, Zhe Wang, Yingbin Liang

* The results of this paper were initially submitted for publication in February 2020 

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Improving Sample Complexity Bounds for Actor-Critic Algorithms

Apr 28, 2020
Tengyu Xu, Zhe Wang, Yingbin Liang

* 30 pages, 0 figure 

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

Feb 26, 2020
Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh


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Multi-Step Model-Agnostic Meta-Learning: Convergence and Improved Algorithms

Feb 20, 2020
Kaiyi Ji, Junjie Yang, Yingbin Liang

* 67 pages, 8 figures 

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Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack

Feb 17, 2020
Ziwei Guan, Kaiyi Ji, Donald J Bucci Jr, Timothy Y Hu, Joseph Palombo, Michael Liston, Yingbin Liang

* Published at AAAI'20 

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Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling

Feb 15, 2020
Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang


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Reanalysis of Variance Reduced Temporal Difference Learning

Jan 10, 2020
Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang

* To appear in ICLR 2020 

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

Oct 27, 2019
Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang

* Published in ICML 2019 

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Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation

Oct 21, 2019
Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang


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Distributed SGD Generalizes Well Under Asynchrony

Sep 29, 2019
Jayanth Regatti, Gaurav Tendolkar, Yi Zhou, Abhishek Gupta, Yingbin Liang


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Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples

Sep 26, 2019
Tengyu Xu, Shaofeng Zou, Yingbin Liang

* To appear in NeurIPS 2019 

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Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization

Feb 11, 2019
Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh


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Finite-Sample Analysis for SARSA and Q-Learning with Linear Function Approximation

Feb 06, 2019
Shaofeng Zou, Tengyu Xu, Yingbin Liang


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SGD Converges to Global Minimum in Deep Learning via Star-convex Path

Jan 02, 2019
Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh

* ICLR2019 

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MR-GAN: Manifold Regularized Generative Adversarial Networks

Nov 22, 2018
Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Yi Zhou, Yingbin Liang, Pramod Varshney

* arXiv admin note: text overlap with arXiv:1706.04156 by other authors 

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Minimax Estimation of Neural Net Distance

Nov 02, 2018
Kaiyi Ji, Yingbin Liang

* To appear in Proc. NIPS 2018 

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

Oct 25, 2018
Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh


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