Qifan Song

According to our database, Qifan Song authored at least 31 papers between 2016 and 2024.

Collaborative distances:

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

2024

Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo.

Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang

Trans. Mach. Learn. Res., 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

Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility.

Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin

CoRR, 2024

Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory.

Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin

CoRR, 2024

Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data.

Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng

CoRR, 2024

Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes.

Jinwon Sohn, Qifan Song, Guang Lin

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Personalized Federated X-armed Bandit.

Wenjie Li, Qifan Song, Jean Honorio

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability.

Rajdeep Haldar, Yue Xing, Qifan Song

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective.

Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Federated X-armed Bandit.

Wenjie Li, Qifan Song, Jean Honorio, Guang Lin

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization.

Wenjie Li, Chi-Hua Wang, Guang Cheng, Qifan Song

Trans. Mach. Learn. Res., 2023

On Neural Network approximation of ideal adversarial attack and convergence of adversarial training.

Rajdeep Haldar, Qifan Song

CoRR, 2023

A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules.

Sehwan Kim, Qifan Song, Faming Liang

CoRR, 2023

Matrix Completion from General Deterministic Sampling Patterns.

Hanbyul Lee, Rahul Mazumder, 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

Support Recovery in Sparse PCA with Non-Random Missing Data.

Hanbyul Lee, Qifan Song, Jean Honorio

CoRR, 2023

2022

Benefit of Interpolation in Nearest Neighbor Algorithms.

Yue Xing, Qifan Song, Guang Cheng

SIAM J. Math. Data Sci., June, 2022

Phase Transition from Clean Training to Adversarial Training.

Yue Xing, Qifan Song, Guang Cheng

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

Why Do Artificially Generated Data Help Adversarial Robustness.

Yue Xing, Qifan Song, Guang Cheng

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

Support Recovery in Sparse PCA with Incomplete Data.

Hanbyul Lee, Qifan Song, Jean Honorio

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

Unlabeled Data Help: Minimax Analysis and Adversarial Robustness.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Consistent Sparse Deep Learning: Theory and Computation.

Yan Sun, Qifan Song, Faming Liang

CoRR, 2021

On the Algorithmic Stability of Adversarial Training.

Yue Xing, Qifan Song, Guang Cheng

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

On the Generalization Properties of Adversarial Training.

Yue Xing, Qifan Song, Guang Cheng

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

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation.

Yue Xing, Qifan Song, Guang Cheng

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

2020

Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors.

Jincheng Bai, Qifan Song, Guang Cheng

CoRR, 2020

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts.

Sehwan Kim, Qifan Song, Faming Liang

CoRR, 2020

Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection.

Qifan Song, Yan Sun, Mao Ye, Faming Liang

CoRR, 2020

Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee.

Jincheng Bai, Qifan Song, Guang Cheng

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

2018

Statistical Optimality of Interpolated Nearest Neighbor Algorithms.

Yue Xing, Qifan Song, Guang Cheng

CoRR, 2018

2016

A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data.

Faming Liang, Jinsu Kim, Qifan Song

Technometrics, 2016