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Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems


Dec 21, 2021
Zongyu Dai, Zhiqi Bu, Qi Long


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Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability


Jul 18, 2021
Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long


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Privacy Amplification via Iteration for Shuffled and Online PNSGD


Jun 20, 2021
Matteo Sordello, Zhiqi Bu, Jinshuo Dong


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Accuracy, Interpretability, and Differential Privacy via Explainable Boosting


Jun 17, 2021
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni

* To be published in ICML 2021. 12 pages, 6 figures 

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On the Convergence of Deep Learning with Differential Privacy


Jun 15, 2021
Zhiqi Bu, Hua Wang, Qi Long, Weijie J. Su


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Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit


May 27, 2021
Zhiqi Bu, Jason Klusowski, Cynthia Rush, Weijie J. Su


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Efficient Designs of SLOPE Penalty Sequences in Finite Dimension


Feb 17, 2021
Yiliang Zhang, Zhiqi Bu

* Accepted to AISTATS 2021 

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Fast and Memory Efficient Differentially Private-SGD via JL Projections


Feb 05, 2021
Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat


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A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks


Oct 25, 2020
Zhiqi Bu, Shiyun Xu, Kan Chen


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Deep Learning with Gaussian Differential Privacy


Dec 10, 2019
Zhiqi Bu, Jinshuo Dong, Qi Long, Weijie J. Su


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Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing


Jul 17, 2019
Zhiqi Bu, Jason Klusowski, Cynthia Rush, Weijie Su


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