Zhiqi Bu

According to our database, Zhiqi Bu authored at least 36 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate.

Zhiqi Bu, Xiaomeng Jin, Bhanukiran Vinzamuri, Anil Ramakrishna, Kai-Wei Chang, Volkan Cevher, Mingyi Hong

CoRR, 2024

DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction.

Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni

CoRR, 2024

DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction.

Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn

CoRR, 2024

Automatic gradient descent with generalized Newton's method.

Zhiqi Bu, Shiyun Xu

CoRR, 2024

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

CoRR, 2024

Pre-training Differentially Private Models with Limited Public Data.

Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis

CoRR, 2024

Differentially Private Bias-Term Fine-tuning of Foundation Models.

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach.

Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy.

Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg, Zhiqi Bu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Differentially Private Optimizers Can Learn Adversarially Robust Models.

Zhiqi Bu, Yuan Zhang

Trans. Mach. Learn. Res., 2023

On the Convergence and Calibration of Deep Learning with Differential Privacy.

Zhiqi Bu, Hua Wang, Zongyu Dai, Qi Long

Trans. Mach. Learn. Res., 2023

Zero redundancy distributed learning with differential privacy.

Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis

CoRR, 2023

On the accuracy and efficiency of group-wise clipping in differentially private optimization.

Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis

CoRR, 2023

Coupling public and private gradient provably helps optimization.

Ruixuan Liu, Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

CoRR, 2023

Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity.

Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

MISNN: Multiple Imputation via Semi-parametric Neural Networks.

Zhiqi Bu, Zongyu Dai, Yiliang Zhang, Qi Long

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger.

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentially Private Optimization on Large Model at Small Cost.

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

Proceedings of the International Conference on Machine Learning, 2023

2022

Accelerating Adversarial Perturbation by 50% with Semi-backward Propagation.

Zhiqi Bu

CoRR, 2022

Differentially Private Bias-Term only Fine-tuning of Foundation Models.

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

CoRR, 2022

Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability.

Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy.

Zhiqi Bu, Jialin Mao, Shiyun Xu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data.

Zongyu Dai, Zhiqi Bu, Qi Long

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing.

Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su

IEEE Trans. Inf. Theory, 2021

On the Convergence of Deep Learning with Differential Privacy.

Zhiqi Bu, Hua Wang, Qi Long, Weijie J. Su

CoRR, 2021

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

Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su

CoRR, 2021

Privacy Amplification via Iteration for Shuffled and Online PNSGD.

Matteo Sordello, Zhiqi Bu, Jinshuo Dong

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing.

Kan Chen, Zhiqi Bu, Shiyun Xu

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Fast and Memory Efficient Differentially Private-SGD via JL Projections.

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Zongyu Dai, Zhiqi Bu, Qi Long

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Accuracy, Interpretability, and Differential Privacy via Explainable Boosting.

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

Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension.

Yiliang Zhang, Zhiqi Bu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks.

Shiyun Xu, Zhiqi Bu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks.

Zhiqi Bu, Shiyun Xu, Kan Chen

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

The Complete Lasso Tradeoff Diagram.

Hua Wang, Yachong Yang, Zhiqi Bu, Weijie J. Su

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Deep Learning with Gaussian Differential Privacy.

Zhiqi Bu, Jinshuo Dong, Qi Long, Weijie J. Su

CoRR, 2019