Qifan Song

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 42

Top Topics

Incomplete Data

Nearest Neighbor

Stochastic Gradient

Algorithmic Stability

Top Venues

Trans. Mach. Learn. Res.

Publications

Rajdeep Haldar, Yue Xing, Qifan Song
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. CoRR (2024)
Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. AISTATS (2024)
Wenjie Li, Qifan Song, Jean Honorio, Guang Lin
Federated X-armed Bandit. AAAI (2024)
Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. CoRR (2024)
Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng
Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. CoRR (2024)
Jinwon Sohn, Qifan Song, Guang Lin
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. AISTATS (2024)
Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. Trans. Mach. Learn. Res. 2024 (2024)
Rajdeep Haldar, Yue Xing, Qifan Song
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. AISTATS (2024)
Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. CoRR (2024)
Wenjie Li, Qifan Song, Jean Honorio
Personalized Federated X-armed Bandit. AISTATS (2024)
Jinwon Sohn, Qifan Song, Guang Lin
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. CoRR (2023)
Rajdeep Haldar, Qifan Song
On Neural Network approximation of ideal adversarial attack and convergence of adversarial training. CoRR (2023)
Wenjie Li, Haoze Li, Jean Honorio, Qifan Song
PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms. CoRR (2023)
Hanbyul Lee, Qifan Song, Jean Honorio
Support Recovery in Sparse PCA with Non-Random Missing Data. CoRR (2023)
Wenjie Li, Qifan Song, Jean Honorio
Personalized Federated X -armed Bandit. CoRR (2023)
Sehwan Kim, Qifan Song, Faming Liang
A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules. CoRR (2023)
Hanbyul Lee, Rahul Mazumder, Qifan Song, Jean Honorio
Matrix Completion from General Deterministic Sampling Patterns. CoRR (2023)
Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. CoRR (2023)
Wenjie Li, Chi-Hua Wang, Guang Cheng, Qifan Song
Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization. Trans. Mach. Learn. Res. 2023 (2023)
Yue Xing, Qifan Song, Guang Cheng
Phase Transition from Clean Training to Adversarial Training. NeurIPS (2022)
Yue Xing, Qifan Song, Guang Cheng
Benefit of Interpolation in Nearest Neighbor Algorithms. SIAM J. Math. Data Sci. 4 (2) (2022)
Hanbyul Lee, Qifan Song, Jean Honorio
Support Recovery in Sparse PCA with Incomplete Data. CoRR (2022)
Hanbyul Lee, Qifan Song, Jean Honorio
Support Recovery in Sparse PCA with Incomplete Data. NeurIPS (2022)
Yue Xing, Qifan Song, Guang Cheng
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. AISTATS (2022)
Wenjie Li, Qifan Song, Jean Honorio, Guang Lin
Federated X-Armed Bandit. CoRR (2022)
Yue Xing, Qifan Song, Guang Cheng
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. CoRR (2022)
Yue Xing, Qifan Song, Guang Cheng
Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR (2022)
Yue Xing, Qifan Song, Guang Cheng
Why Do Artificially Generated Data Help Adversarial Robustness. NeurIPS (2022)
Yue Xing, Qifan Song, Guang Cheng
On the Algorithmic Stability of Adversarial Training. NeurIPS (2021)
Yan Sun, Qifan Song, Faming Liang
Consistent Sparse Deep Learning: Theory and Computation. CoRR (2021)
Yue Xing, Qifan Song, Guang Cheng
On the Generalization Properties of Adversarial Training. AISTATS (2021)
Yue Xing, Qifan Song, Guang Cheng
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. AISTATS (2021)
Qifan Song, Yan Sun, Mao Ye, Faming Liang
Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection. CoRR (2020)
Jincheng Bai, Qifan Song, Guang Cheng
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. CoRR (2020)
Yue Xing, Qifan Song, Guang Cheng
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. CoRR (2020)
Sehwan Kim, Qifan Song, Faming Liang
Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts. CoRR (2020)
Yue Xing, Qifan Song, Guang Cheng
On the Generalization Properties of Adversarial Training. CoRR (2020)
Jincheng Bai, Qifan Song, Guang Cheng
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors. CoRR (2020)
Jincheng Bai, Qifan Song, Guang Cheng
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. NeurIPS (2020)
Yue Xing, Qifan Song, Guang Cheng
Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR (2019)
Yue Xing, Qifan Song, Guang Cheng
Statistical Optimality of Interpolated Nearest Neighbor Algorithms. CoRR (2018)
Faming Liang, Jinsu Kim, Qifan Song
A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data. Technometrics 58 (3) (2016)