Zhiqi Bu

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 50

Top Topics

Statistical Estimation

Differential Privacy

Top Venues

Publications

Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation. CoRR (2024)
Zhiqi Bu, Shiyun Xu
Automatic gradient descent with generalized Newton's method. CoRR (2024)
Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. ICLR (2024)
Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg, Zhiqi Bu
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy. ICLR (2024)
Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis
Pre-training Differentially Private Models with Limited Public Data. CoRR (2024)
Xinwei Zhang, Zhiqi Bu, Zhiwei Steven Wu, Mingyi Hong
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. CoRR (2023)
Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis
Zero redundancy distributed learning with differential privacy. CoRR (2023)
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. ECML/PKDD (3) (2023)
Zhiqi Bu, Zongyu Dai, Yiliang Zhang, Qi Long
MISNN: Multiple Imputation via Semi-parametric Neural Networks. CoRR (2023)
Zhiqi Bu, Zongyu Dai, Yiliang Zhang, Qi Long
MISNN: Multiple Imputation via Semi-parametric Neural Networks. PAKDD (1) (2023)
Zhiqi Bu, Yuan Zhang
Differentially Private Optimizers Can Learn Adversarially Robust Models. Trans. Mach. Learn. Res. 2023 (2023)
Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis
On the accuracy and efficiency of group-wise clipping in differentially private optimization. CoRR (2023)
Zhiqi Bu, Hua Wang, Zongyu Dai, Qi Long
On the Convergence and Calibration of Deep Learning with Differential Privacy. Trans. Mach. Learn. Res. 2023 (2023)
Ruixuan Liu, Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Coupling public and private gradient provably helps optimization. CoRR (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. NeurIPS (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Optimization on Large Model at Small Cost. ICML (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Bias-Term only Fine-tuning of Foundation Models. CoRR (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. CoRR (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Optimization on Large Model at Small Cost. CoRR (2022)
Zhiqi Bu, Jialin Mao, Shiyun Xu
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy. NeurIPS (2022)
Yuan Zhang, Zhiqi Bu
Differentially Private Optimizers Can Learn Adversarially Robust Models. CoRR (2022)
Zongyu Dai, Zhiqi Bu, Qi Long
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data. CoRR (2022)
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. CoRR (2022)
Zongyu Dai, Zhiqi Bu, Qi Long
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data. ACML (2022)
Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability. ECML/PKDD (4) (2022)
Zhiqi Bu, Jialin Mao, Shiyun Xu
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy. CoRR (2022)
Zhiqi Bu
Accelerating Adversarial Perturbation by 50% with Semi-backward Propagation. CoRR (2022)
Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
Fast and Memory Efficient Differentially Private-SGD via JL Projections. CoRR (2021)
Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability. CoRR (2021)
Zhiqi Bu, Hua Wang, Qi Long, Weijie J. Su
On the Convergence of Deep Learning with Differential Privacy. CoRR (2021)
Matteo Sordello, Zhiqi Bu, Jinshuo Dong
Privacy Amplification via Iteration for Shuffled and Online PNSGD. ECML/PKDD (2) (2021)
Kan Chen, Zhiqi Bu, Shiyun Xu
Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing. ECML/PKDD (3) (2021)
Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
Fast and Memory Efficient Differentially Private-SGD via JL Projections. NeurIPS (2021)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. IEEE Trans. Inf. Theory 67 (1) (2021)
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting. ICML (2021)
Matteo Sordello, Zhiqi Bu, Jinshuo Dong
Privacy Amplification via Iteration for Shuffled and Online PNSGD. CoRR (2021)
Yiliang Zhang, Zhiqi Bu
Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension. AISTATS (2021)
Zongyu Dai, Zhiqi Bu, Qi Long
Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems. CoRR (2021)
Yiliang Zhang, Zhiqi Bu
Efficient Designs of SLOPE Penalty Sequences in Finite Dimension. CoRR (2021)
Zhiqi Bu, Shiyun Xu, Kan Chen
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks. AISTATS (2021)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit. CoRR (2021)
Shiyun Xu, Zhiqi Bu
DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks. AISTATS (2021)
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting. CoRR (2021)
Zongyu Dai, Zhiqi Bu, Qi Long
Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems. ICMLA (2021)
Zhiqi Bu, Shiyun Xu, Kan Chen
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks. CoRR (2020)
Hua Wang, Yachong Yang, Zhiqi Bu, Weijie J. Su
The Complete Lasso Tradeoff Diagram. CoRR (2020)
Hua Wang, Yachong Yang, Zhiqi Bu, Weijie J. Su
The Complete Lasso Tradeoff Diagram. NeurIPS (2020)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. CoRR (2019)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. NeurIPS (2019)
Zhiqi Bu, Jinshuo Dong, Qi Long, Weijie J. Su
Deep Learning with Gaussian Differential Privacy. CoRR (2019)