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Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks


Oct 13, 2020
Xin Xing, Yu Gui, Chenguang Dai, Jun S. Liu

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Minimax Nonparametric Two-sample Test


Nov 08, 2019
Xin Xing, Zuofeng Shang, Pang Du, Ping Ma, Wenxuan Zhong, Jun S. Liu

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* 56 pages 

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The Wang-Landau Algorithm as Stochastic Optimization and its Acceleration


Jul 27, 2019
Chenguang Dai, Jun S. Liu

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* 4 pages, 1 figure 

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Generative Parameter Sampler For Scalable Uncertainty Quantification


Jun 02, 2019
Minsuk Shin, Young Lee, Jun S. Liu

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Signed Support Recovery for Single Index Models in High-Dimensions


Jun 23, 2016
Matey Neykov, Qian Lin, Jun S. Liu

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* 38 pages, 7 figures; 1 table; data set analysis added; typos corrected 

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L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs


Jun 23, 2016
Matey Neykov, Jun S. Liu, Tianxi Cai

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* 36 pages; 6 figures; typos corrected; clearer notation introduced 

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A Unified Theory of Confidence Regions and Testing for High Dimensional Estimating Equations


Jun 23, 2016
Matey Neykov, Yang Ning, Jun S. Liu, Han Liu

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* 67 pages, 2 tables, 1 figure 

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Interpretable Selection and Visualization of Features and Interactions Using Bayesian Forests


Feb 07, 2016
Viktoriya Krakovna, Jiong Du, Jun S. Liu

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* R package: github.com/vkrakovna/sbfc 

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