Qifan Song - RankMe

55 papers A* 6A 8Journal 41

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adversarial Vulnerability from On-Manifold Inseparability and Poor Off-Manifold Convergence. Trans. Mach. Learn. Res. Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin
2026	J	`jnl`	Generalized Discrete Diffusion with Self-Correction. CoRR Linxuan Wang, Ziyi Wang, Yikun Bai, Wei Deng, Guang Lin, Qifan Song
2026	J	`jnl`	Task-tailored Pre-processing: Fair Downstream Supervised Learning. CoRR Jinwon Sohn, Guang Lin, Qifan Song
2026	J	`jnl`	f-GRPO and Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment. CoRR Rajdeep Haldar, Lantao Mei, Guang Lin, Yue Xing, Qifan Song
2025	J	`jnl`	Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. J. Comput. Graph. Stat. Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
2025	J	`jnl`	Knowledge Distillation Detection for Open-weights Models. CoRR Qin Shi, Amber Yijia Zheng, Qifan Song, Raymond A. Yeh
2025	J	`jnl`	LLM Safety Alignment is Divergence Estimation in Disguise. CoRR Rajdeep Haldar, Ziyi Wang, Qifan Song, Guang Lin, Yue Xing
2025	J	`jnl`	On Neural Network Approximation of Ideal Adversarial Attack and Convergence of Adversarial Training. SIAM J. Math. Data Sci. Rajdeep Haldar, Qifan Song
2025	J	`jnl`	SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions. CoRR Ziyi Wang, Nan Jiang, Guang Lin, Qifan Song
2024	J	`jnl`	Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility. CoRR Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin
2024	J	`jnl`	Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. CoRR Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
2024	J	`jnl`	Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. CoRR Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng
2024	A	`conf`	Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. AISTATS Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
2024	J	`jnl`	Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. CoRR Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
2024	A	`conf`	Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. AISTATS Rajdeep Haldar, Yue Xing, Qifan Song
2024	J	`jnl`	Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. CoRR Rajdeep Haldar, Yue Xing, Qifan Song
2024	J	`jnl`	Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. Trans. Mach. Learn. Res. Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
2024	A	`conf`	Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. AISTATS Jinwon Sohn, Qifan Song, Guang Lin
2024	A*	`conf`	Federated X-armed Bandit. AAAI Wenjie Li, Qifan Song, Jean Honorio, Guang Lin
2024	J	`jnl`	Parallelly Tempered Generative Adversarial Networks. CoRR Jinwon Sohn, Qifan Song
2024	A	`conf`	Personalized Federated X-armed Bandit. AISTATS Wenjie Li, Qifan Song, Jean Honorio
2024	J	`jnl`	PyXAB - A Python Library for \mathcal{X}-Armed Bandit and Online Blackbox Optimization Algorithms. J. Open Source Softw. Wenjie Li, Haoze Li, Qifan Song, Jean Honorio
2024	A	`conf`	Support Recovery in Sparse PCA with General Missing Data. UAI Hanbyul Lee, Qifan Song, Jean Honorio
2023	J	`jnl`	A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules. CoRR Sehwan Kim, Qifan Song, Faming Liang
2023	J	`jnl`	Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. CoRR Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
2023	J	`jnl`	Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. CoRR Jinwon Sohn, Qifan Song, Guang Lin
2023	J	`jnl`	Matrix Completion from General Deterministic Sampling Patterns. CoRR Hanbyul Lee, Rahul Mazumder, Qifan Song, Jean Honorio
2023	J	`jnl`	On Neural Network approximation of ideal adversarial attack and convergence of adversarial training. CoRR Rajdeep Haldar, Qifan Song
2023	J	`jnl`	Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization. Trans. Mach. Learn. Res. Wenjie Li, Chi-hua Wang, Guang Cheng, Qifan Song
2023	J	`jnl`	Personalized Federated X -armed Bandit. CoRR Wenjie Li, Qifan Song, Jean Honorio
2023	J	`jnl`	PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms. CoRR Wenjie Li, Haoze Li, Jean Honorio, Qifan Song
2023	J	`jnl`	Support Recovery in Sparse PCA with Non-Random Missing Data. CoRR Hanbyul Lee, Qifan Song, Jean Honorio
2022	J	`jnl`	Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR Yue Xing, Qifan Song, Guang Cheng
2022	J	`jnl`	Benefit of Interpolation in Nearest Neighbor Algorithms. SIAM J. Math. Data Sci. Yue Xing, Qifan Song, Guang Cheng
2022	J	`jnl`	Federated X-Armed Bandit. CoRR Wenjie Li, Qifan Song, Jean Honorio, Guang Lin
2022	A*	`conf`	Phase Transition from Clean Training to Adversarial Training. NeurIPS Yue Xing, Qifan Song, Guang Cheng
2022	A*	`conf`	Support Recovery in Sparse PCA with Incomplete Data. NeurIPS Hanbyul Lee, Qifan Song, Jean Honorio
2022	J	`jnl`	Support Recovery in Sparse PCA with Incomplete Data. CoRR Hanbyul Lee, Qifan Song, Jean Honorio
2022	A	`conf`	Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. AISTATS Yue Xing, Qifan Song, Guang Cheng
2022	J	`jnl`	Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. CoRR Yue Xing, Qifan Song, Guang Cheng
2022	A*	`conf`	Why Do Artificially Generated Data Help Adversarial Robustness. NeurIPS Yue Xing, Qifan Song, Guang Cheng
2021	J	`jnl`	Consistent Sparse Deep Learning: Theory and Computation. CoRR Yan Sun, Qifan Song, Faming Liang
2021	A*	`conf`	On the Algorithmic Stability of Adversarial Training. NeurIPS Yue Xing, Qifan Song, Guang Cheng
2021	A	`conf`	On the Generalization Properties of Adversarial Training. AISTATS Yue Xing, Qifan Song, Guang Cheng
2021	A	`conf`	Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. AISTATS Yue Xing, Qifan Song, Guang Cheng
2020	A*	`conf`	Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. NeurIPS Jincheng Bai, Qifan Song, Guang Cheng
2020	J	`jnl`	Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee. CoRR Jincheng Bai, Qifan Song, Guang Cheng
2020	J	`jnl`	Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection. CoRR Qifan Song, Yan Sun, Mao Ye, Faming Liang
2020	J	`jnl`	Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors. CoRR Jincheng Bai, Qifan Song, Guang Cheng
2020	J	`jnl`	On the Generalization Properties of Adversarial Training. CoRR Yue Xing, Qifan Song, Guang Cheng
2020	J	`jnl`	Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. CoRR Yue Xing, Qifan Song, Guang Cheng
2020	J	`jnl`	Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts. CoRR Sehwan Kim, Qifan Song, Faming Liang
2019	J	`jnl`	Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR Yue Xing, Qifan Song, Guang Cheng
2018	J	`jnl`	Statistical Optimality of Interpolated Nearest Neighbor Algorithms. CoRR Yue Xing, Qifan Song, Guang Cheng
2016	J	`jnl`	A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data. Technometrics Faming Liang, Jinsu Kim, Qifan Song