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Journal Articles
- 2024
[j5]Wenjie Li
, Haoze Li, Qifan Song, Jean Honorio:
PyXAB - A Python Library for \mathcal{X}-Armed Bandit and Online Blackbox Optimization Algorithms. J. Open Source Softw. 9(102): 6507 (2024)- [j4]Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang:
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j3]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) - 2022
- [j2]Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. SIAM J. Math. Data Sci. 4(2): 935-956 (2022) - 2016
- [j1]Faming Liang, Jinsu Kim, Qifan Song:
A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data. Technometrics 58(3): 304-318 (2016)
Conference and Workshop Papers
- 2024
- [c13]Wenjie Li, Qifan Song, Jean Honorio, Guang Lin:
Federated X-armed Bandit. AAAI 2024: 13628-13636 - [c12]Wenjie Li, Qifan Song, Jean Honorio:
Personalized Federated X-armed Bandit. AISTATS 2024: 37-45 - [c11]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: 199-207 - [c10]Rajdeep Haldar, Yue Xing, Qifan Song:
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. AISTATS 2024: 1090-1098 - [c9]Jinwon Sohn, Qifan Song, Guang Lin:
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. AISTATS 2024: 1594-1602 - 2022
- [c8]Yue Xing, Qifan Song, Guang Cheng:
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. AISTATS 2022: 136-168 - [c7]Hanbyul Lee, Qifan Song, Jean Honorio:
Support Recovery in Sparse PCA with Incomplete Data. NeurIPS 2022 - [c6]Yue Xing, Qifan Song, Guang Cheng:
Why Do Artificially Generated Data Help Adversarial Robustness. NeurIPS 2022 - [c5]Yue Xing, Qifan Song, Guang Cheng:
Phase Transition from Clean Training to Adversarial Training. NeurIPS 2022 - 2021
- [c4]Yue Xing, Qifan Song, Guang Cheng:
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. AISTATS 2021: 496-504 - [c3]Yue Xing, Qifan Song, Guang Cheng:
On the Generalization Properties of Adversarial Training. AISTATS 2021: 505-513 - [c2]Yue Xing, Qifan Song, Guang Cheng:
On the Algorithmic Stability of Adversarial Training. NeurIPS 2021: 26523-26535 - 2020
- [c1]Jincheng Bai, Qifan Song, Guang Cheng:
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. NeurIPS 2020
Informal and Other Publications
- 2024
- [i26]Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng:
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. CoRR abs/2401.15248 (2024) - [i25]Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng:
Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. CoRR abs/2402.00743 (2024) - [i24]Rajdeep Haldar, Yue Xing, Qifan Song:
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. CoRR abs/2403.03967 (2024) - [i23]Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin:
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. CoRR abs/2407.06935 (2024) - [i22]Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin:
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility. CoRR abs/2410.06921 (2024) - 2023
- [i21]Hanbyul Lee, Qifan Song, Jean Honorio:
Support Recovery in Sparse PCA with Non-Random Missing Data. CoRR abs/2302.01535 (2023) - [i20]Wenjie Li, Haoze Li, Jean Honorio, Qifan Song:
PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms. CoRR abs/2303.04030 (2023) - [i19]Hanbyul Lee, Rahul Mazumder, Qifan Song, Jean Honorio:
Matrix Completion from General Deterministic Sampling Patterns. CoRR abs/2306.02283 (2023) - [i18]Sehwan Kim, Qifan Song, Faming Liang:
A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules. CoRR abs/2306.13641 (2023) - [i17]Rajdeep Haldar, Qifan Song:
On Neural Network approximation of ideal adversarial attack and convergence of adversarial training. CoRR abs/2307.16099 (2023) - [i16]Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang:
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. CoRR abs/2310.16320 (2023) - [i15]Wenjie Li, Qifan Song, Jean Honorio:
Personalized Federated X -armed Bandit. CoRR abs/2310.16323 (2023) - [i14]Jinwon Sohn, Qifan Song, Guang Lin:
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. CoRR abs/2311.05866 (2023) - 2022
- [i13]Yue Xing, Qifan Song, Guang Cheng:
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. CoRR abs/2202.06996 (2022) - [i12]Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR abs/2202.11817 (2022) - [i11]Hanbyul Lee, Qifan Song, Jean Honorio:
Support Recovery in Sparse PCA with Incomplete Data. CoRR abs/2205.15215 (2022) - [i10]Wenjie Li, Qifan Song, Jean Honorio, Guang Lin:
Federated X-Armed Bandit. CoRR abs/2205.15268 (2022) - 2021
- [i9]Yan Sun, Qifan Song, Faming Liang:
Consistent Sparse Deep Learning: Theory and Computation. CoRR abs/2102.13229 (2021) - 2020
- [i8]Qifan Song, Yan Sun, Mao Ye, Faming Liang:
Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection. CoRR abs/2002.02919 (2020) - [i7]Yue Xing, Qifan Song, Guang Cheng:
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. CoRR abs/2002.05304 (2020) - [i6]Yue Xing, Qifan Song, Guang Cheng:
On the Generalization Properties of Adversarial Training. CoRR abs/2008.06631 (2020) - [i5]Sehwan Kim, Qifan Song, Faming Liang:
Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts. CoRR abs/2009.09535 (2020) - [i4]Jincheng Bai, Qifan Song, Guang Cheng:
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors. CoRR abs/2010.12887 (2020) - [i3]Jincheng Bai, Qifan Song, Guang Cheng:
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. CoRR abs/2011.07439 (2020) - 2019
- [i2]Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR abs/1909.11720 (2019) - 2018
- [i1]Yue Xing, Qifan Song, Guang Cheng:
Statistical Optimality of Interpolated Nearest Neighbor Algorithms. CoRR abs/1810.02814 (2018)
Coauthor Index
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