A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data. - Faming Liang; Jinsu Kim; Qifan Song (Technometrics, 2016)

Statistical Optimality of Interpolated Nearest Neighbor Algorithms. - Yue Xing 002; Qifan Song; Guang Cheng 003 (CoRR, 2018)

Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. - Jincheng Bai; Qifan Song; Guang Cheng 003 (NeurIPS, 2020)

Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection. - Qifan Song; Yan Sun 011; Mao Ye; Faming Liang (CoRR, 2020)

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts. - Sehwan Kim; Qifan Song; Faming Liang (CoRR, 2020)

Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors. - Jincheng Bai; Qifan Song; Guang Cheng 003 (CoRR, 2020)

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. - Yue Xing 002; Qifan Song; Guang Cheng 003 (AISTATS, 2021)

On the Generalization Properties of Adversarial Training. - Yue Xing 002; Qifan Song; Guang Cheng 003 (AISTATS, 2021)

On the Algorithmic Stability of Adversarial Training. - Yue Xing 002; Qifan Song; Guang Cheng 003 (NeurIPS, 2021)

Consistent Sparse Deep Learning: Theory and Computation. - Yan Sun 011; Qifan Song; Faming Liang (CoRR, 2021)

Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. - Yue Xing 002; Qifan Song; Guang Cheng 003 (AISTATS, 2022)

Support Recovery in Sparse PCA with Incomplete Data. - Hanbyul Lee 001; Qifan Song; Jean Honorio (NeurIPS, 2022)

Why Do Artificially Generated Data Help Adversarial Robustness. - Yue Xing 002; Qifan Song; Guang Cheng 003 (NeurIPS, 2022)

Phase Transition from Clean Training to Adversarial Training. - Yue Xing 002; Qifan Song; Guang Cheng 003 (NeurIPS, 2022)

Benefit of Interpolation in Nearest Neighbor Algorithms. - Yue Xing 002; Qifan Song; Guang Cheng 003 (SIAM J. Math. Data Sci., 2022)

Support Recovery in Sparse PCA with Non-Random Missing Data. - Hanbyul Lee 001; Qifan Song; Jean Honorio (CoRR, 2023)

PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms. - Wenjie Li; Haoze Li; Jean Honorio; Qifan Song (CoRR, 2023)

Matrix Completion from General Deterministic Sampling Patterns. - Hanbyul Lee 001; Rahul Mazumder; Qifan Song; Jean Honorio (CoRR, 2023)

A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules. - Sehwan Kim; Qifan Song; Faming Liang (CoRR, 2023)

On Neural Network approximation of ideal adversarial attack and convergence of adversarial training. - Rajdeep Haldar; Qifan Song (CoRR, 2023)

Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. - Jinwon Sohn; Qifan Song; Guang Lin 001 (CoRR, 2023)

Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization. - Wenjie Li; Chi-Hua Wang; Guang Cheng 003; Qifan Song (Trans. Mach. Learn. Res., 2023)

Federated X-armed Bandit. - Wenjie Li; Qifan Song; Jean Honorio; Guang Lin 001 (AAAI, 2024)

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. - Yue Xing 002; Xiaofeng Lin 005; Qifan Song; Yi Xu 011; Belinda Zeng; Guang Cheng 003 (AISTATS, 2024)

Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. - Rajdeep Haldar; Yue Xing 002; Qifan Song (AISTATS, 2024)

Personalized Federated X-armed Bandit. - Wenjie Li; Qifan Song; Jean Honorio (AISTATS, 2024)

Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. - Jinwon Sohn; Qifan Song; Guang Lin (AISTATS, 2024)

Support Recovery in Sparse PCA with General Missing Data. - Hanbyul Lee 001; Qifan Song; Jean Honorio (UAI, 2024)

Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. - Yue Xing 002; Xiaofeng Lin 005; Namjoon Suh; Qifan Song; Guang Cheng 003 (CoRR, 2024)

Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility. - Rajdeep Haldar; Yue Xing 002; Qifan Song; Guang Lin 001 (CoRR, 2024)

Parallelly Tempered Generative Adversarial Networks. - Jinwon Sohn; Qifan Song (CoRR, 2024)

PyXAB - A Python Library for mathcal{X}-Armed Bandit and Online Blackbox Optimization Algorithms. - Wenjie Li; Haoze Li; Qifan Song; Jean Honorio (J. Open Source Softw., 2024)

Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. - Ziyi Wang; Yujie Chen; Qifan Song; Ruqi Zhang (Trans. Mach. Learn. Res., 2024)

Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. - Jiajun Liang; Qian Zhang 067; Wei Deng 002; Qifan Song; Guang Lin 001 (J. Comput. Graph. Stat., 2025)

LLM Safety Alignment is Divergence Estimation in Disguise. - Rajdeep Haldar; Ziyi Wang; Qifan Song; Guang Lin 001; Yue Xing 002 (CoRR, 2025)