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Provably-Efficient Double Q-Learning

Jul 09, 2020
Wentao Weng, Harsh Gupta, Niao He, Lei Ying, R. Srikant

* 15 pages, 3 figures, 1 table 

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Biased Stochastic Gradient Descent for Conditional Stochastic Optimization

Feb 25, 2020
Yifan Hu, Siqi Zhang, Xin Chen, Niao He


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Periodic Q-Learning

Feb 23, 2020
Donghwan Lee, Niao He


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Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems

Feb 22, 2020
Junchi Yang, Negar Kiyavash, Niao He


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A Unified Switching System Perspective and O.D.E. Analysis of Q-Learning Algorithms

Dec 12, 2019
Donghwan Lee, Niao He


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Optimization for Reinforcement Learning: From Single Agent to Cooperative Agents

Dec 01, 2019
Donghwan Lee, Niao He, Parameswaran Kamalaruban, Volkan Cevher


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Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization

May 28, 2019
Yifan Hu, Xin Chen, Niao He


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Exponential Family Estimation via Adversarial Dynamics Embedding

Apr 27, 2019
Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans

* 66 figures, 25 pages; preliminary version published in NeurIPS2018 Bayesian Deep Learning Workshop 

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Target-Based Temporal Difference Learning

Apr 24, 2019
Donghwan Lee, Niao He


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Quadratic Decomposable Submodular Function Minimization: Theory and Practice

Feb 26, 2019
Pan Li, Niao He, Olgica Milenkovic

* A part of the work appeared in NeurIPS 2018. The current version is under review for a journal. arXiv admin note: substantial text overlap with arXiv:1806.09842 

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Kernel Exponential Family Estimation via Doubly Dual Embedding

Nov 06, 2018
Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He

* 22 pages, 20 figures 

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Quadratic Decomposable Submodular Function Minimization

Oct 11, 2018
Pan Li, Niao He, Olgica Milenkovic

* A part of this work will be presented in NIPS2018 

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SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation

Jun 05, 2018
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song

* 28 pages, 13 figures. To appear at the 35th International Conference on Machine Learning (ICML 2018) 

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Nonparametric Hawkes Processes: Online Estimation and Generalization Bounds

Jan 25, 2018
Yingxiang Yang, Jalal Etesami, Niao He, Negar Kiyavash


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Boosting the Actor with Dual Critic

Dec 29, 2017
Bo Dai, Albert Shaw, Niao He, Lihong Li, Le Song

* 21 pages, 9 figures 

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Stochastic Generative Hashing

Aug 12, 2017
Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song

* 21 pages, 40 figures 

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Learning from Conditional Distributions via Dual Embeddings

Dec 31, 2016
Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song

* 24 pages, 11 figures 

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Fast and Simple Optimization for Poisson Likelihood Models

Aug 03, 2016
Niao He, Zaid Harchaoui, Yichen Wang, Le Song


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Provable Bayesian Inference via Particle Mirror Descent

May 05, 2016
Bo Dai, Niao He, Hanjun Dai, Le Song

* 38 pages, 26 figures 

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Scalable Kernel Methods via Doubly Stochastic Gradients

Sep 10, 2015
Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song

* 32 pages, 22 figures 

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Semi-proximal Mirror-Prox for Nonsmooth Composite Minimization

Jul 06, 2015
Niao He, Zaid Harchaoui


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Stochastic ADMM for Nonsmooth Optimization

Jan 22, 2013
Hua Ouyang, Niao He, Alexander Gray

* A short version of this paper appears in the 5th NIPS Workshop on Optimization for Machine Learning, Lake Tahoe, Nevada, USA, 2012 

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