Bu, Zhiqi

31 publications

ICLR 2025 DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni

ICLR 2025 Gradient Descent with Generalized Newton’s Method Zhiqi Bu, Shiyun Xu

ICLR 2025 MAP: Low-Compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio

ICLR 2025 Towards Hyperparameter-Free Optimization with Differential Privacy Ruixuan Liu, Zhiqi Bu

NeurIPS 2024 DOPPLER: Differentially Private Optimizers with Low-Pass Filter for Privacy Noise Reduction Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn

NeurIPSW 2024 DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni

ICML 2024 Differentially Private Bias-Term Fine-Tuning of Foundation Models Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

ICLR 2024 Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong

NeurIPSW 2024 MAP: Model Merging with Amortized Pareto Front Using Limited Computation Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio

NeurIPS 2024 Pre-Training Differentially Private Models with Limited Public Data Zhiqi Bu, Xinwei Zhang, Sheng Zha, Mingyi Hong, George Karypis

ICLR 2024 Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Emily Redberg, Zhiqi Bu

NeurIPS 2023 Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

ICML 2023 Differentially Private Optimization on Large Model at Small Cost Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

TMLR 2023 Differentially Private Optimizers Can Learn Adversarially Robust Models Zhiqi Bu, Yuan Zhang

TMLR 2023 On the Convergence and Calibration of Deep Learning with Differential Privacy Zhiqi Bu, Hua Wang, Zongyu Dai, Qi Long

ECML-PKDD 2023 Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett

ICLRW 2023 Zero Redundancy Distributed Learning with Differential Privacy Zhiqi Bu, Justin Chiu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis

ECML-PKDD 2022 Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long

NeurIPSW 2022 Differentially Private Bias-Term Only Fine-Tuning of Foundation Models Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

ACML 2022 Multiple Imputation with Neural Network Gaussian Process for High-Dimensional Incomplete Data Zongyu Dai, Zhiqi Bu, Qi Long

NeurIPS 2022 Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu, Jialin Mao, Shiyun Xu

ICLRW 2022 Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett

AISTATS 2021 A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks Zhiqi Bu, Shiyun Xu, Kan Chen

AISTATS 2021 DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks Shiyun Xu, Zhiqi Bu

AISTATS 2021 Efficient Designs of SLOPE Penalty Sequences in Finite Dimension Yiliang Zhang, Zhiqi Bu

ICML 2021 Accuracy, Interpretability, and Differential Privacy via Explainable Boosting Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni

ECML-PKDD 2021 Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing Kan Chen, Zhiqi Bu, Shiyun Xu

NeurIPS 2021 Fast and Memory Efficient Differentially Private-SGD via JL Projections Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Hanwen Shen, Uthaipon Tantipongpipat

ECML-PKDD 2021 Privacy Amplification via Iteration for Shuffled and Online PNSGD Matteo Sordello, Zhiqi Bu, Jinshuo Dong

NeurIPS 2020 The Complete Lasso Tradeoff Diagram Hua Wang, Yachong Yang, Zhiqi Bu, Weijie Su

NeurIPS 2019 Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing Zhiqi Bu, Jason Klusowski, Cynthia Rush, Weijie Su