Qifan Song

Guang Lin

CoRR, January, 2026

Adversarial Vulnerability from On-Manifold Inseparability and Poor Off-Manifold Convergence.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2026

2025

SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions.

[BibT_eX]

[DOI]

CoRR, October, 2025

On Neural Network Approximation of Ideal Adversarial Attack and Convergence of Adversarial Training.

[BibT_eX]

[DOI]

Rajdeep Haldar

SIAM J. Math. Data Sci., 2025

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

[BibT_eX]

[DOI]

J. Comput. Graph. Stat., 2025

Knowledge Distillation Detection for Open-weights Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

LLM Safety Alignment is Divergence Estimation in Disguise.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

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

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

PyXAB - A Python Library for \mathcal{X}-Armed Bandit and Online Blackbox Optimization Algorithms.

[BibT_eX]

[DOI]

J. Open Source Softw., 2024

Parallelly Tempered Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility.

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

Support Recovery in Sparse PCA with General Missing Data.

[BibT_eX]

[DOI]

Hanbyul Lee

Proceedings of the Uncertainty in Artificial Intelligence, 2024

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

[BibT_eX]

[DOI]

Guang Lin

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

Personalized Federated X-armed Bandit.

[BibT_eX]

[DOI]

Wenjie Li

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

Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability.

[BibT_eX]

[DOI]

Rajdeep Haldar

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

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

[BibT_eX]

[DOI]

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

Federated X-armed Bandit.

[BibT_eX]

[DOI]

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

2023

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

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

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

[BibT_eX]

[DOI]

Guang Lin

CoRR, 2023

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

[BibT_eX]

[DOI]

Sehwan Kim

CoRR, 2023

Matrix Completion from General Deterministic Sampling Patterns.

[BibT_eX]

[DOI]

CoRR, 2023

PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Hanbyul Lee

CoRR, 2023

2022

Benefit of Interpolation in Nearest Neighbor Algorithms.

[BibT_eX]

[DOI]

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

Phase Transition from Clean Training to Adversarial Training.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Hanbyul Lee

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.

[BibT_eX]

[DOI]

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

2021

Consistent Sparse Deep Learning: Theory and Computation.

[BibT_eX]

[DOI]

Yan Sun

CoRR, 2021

On the Algorithmic Stability of Adversarial Training.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation.

[BibT_eX]

[DOI]

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

2020

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

[BibT_eX]

[DOI]

Jincheng Bai

CoRR, 2020

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts.

[BibT_eX]

[DOI]

Sehwan Kim

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee.

[BibT_eX]

[DOI]

Jincheng Bai

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.

[BibT_eX]

[DOI]

CoRR, 2018

2016

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

[BibT_eX]

[DOI]

Jinsu Kim