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Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications

Dec 07, 2020
Rong Zhu, Andreas Pfadler, Ziniu Wu, Yuxing Han, Xiaoke Yang, Feng Ye, Zhenping Qian, Jingren Zhou, Bin Cui


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Self-correcting Q-Learning

Dec 02, 2020
Rong Zhu, Mattia Rigotti

* Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21) 

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FSPN: A New Class of Probabilistic Graphical Model

Nov 20, 2020
Ziniu Wu, Rong Zhu, Andreas Pfadler, Yuxing Han, Jiangneng Li, Zhengping Qian, Kai Zeng, Jingren Zhou

* 16 pages 

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FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation

Nov 18, 2020
Rong Zhu, Ziniu Wu, Yuxing Han, Kai Zeng, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Bin Cui

* 13 pages 

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Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data

Jul 17, 2018
E. Kelly Buchanan, Ian Kinsella, Ding Zhou, Rong Zhu, Pengcheng Zhou, Felipe Gerhard, John Ferrante, Ying Ma, Sharon Kim, Mohammed Shaik, Yajie Liang, Rongwen Lu, Jacob Reimer, Paul Fahey, Taliah Muhammad, Graham Dempsey, Elizabeth Hillman, Na Ji, Andreas Tolias, Liam Paninski

* 36 pages, 18 figures 

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Subsampled Optimization: Statistical Guarantees, Mean Squared Error Approximation, and Sampling Method

Apr 10, 2018
Rong Zhu, Jiming Jiang


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Optimal Subsampling for Large Sample Logistic Regression

Mar 07, 2018
HaiYing Wang, Rong Zhu, Ping Ma


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Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares

Mar 02, 2018
Rong Zhu

* 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain 

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Poisson Subsampling Algorithms for Large Sample Linear Regression in Massive Data

Nov 23, 2015
Rong Zhu

* This paper has been withdrawn by the author due to an improper citation 

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Optimal Subsampling Approaches for Large Sample Linear Regression

Nov 23, 2015
Rong Zhu, Ping Ma, Michael W. Mahoney, Bin Yu

* This paper has been withdrawn by the author due to the incompleteness of this draft 

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