Bai Li

According to our database, Bai Li authored at least 11 papers between 2018 and 2021.

Collaborative distances:

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

2021

Privacy and Robustness of Deep Neural Networks.

Bai Li

PhD thesis, 2021

2020

Towards Understanding Fast Adversarial Training.

Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin

CoRR, 2020

Towards Practical Lottery Ticket Hypothesis for Adversarial Training.

Bai Li, Shiqi Wang, Yunhan Jia, Yantao Lu, Zhenyu Zhong, Lawrence Carin, Suman Jana

CoRR, 2020

Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction.

Yantao Lu, Yunhan Jia, Jianyu Wang, Bai Li, Weiheng Chai, Lawrence Carin, Senem Velipasalar

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Graph-Driven Generative Models for Heterogeneous Multi-Task Learning.

Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

On Norm-Agnostic Robustness of Adversarial Training.

Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin

CoRR, 2019

Certified Adversarial Robustness with Additive Noise.

Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Improving Sequence-to-Sequence Learning via Optimal Transport.

Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin

Proceedings of the 7th International Conference on Learning Representations, 2019

On Connecting Stochastic Gradient MCMC and Differential Privacy.

Bai Li, Changyou Chen, Hao Liu, Lawrence Carin

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Second-Order Adversarial Attack and Certifiable Robustness.

Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin

CoRR, 2018

A Unified Particle-Optimization Framework for Scalable Bayesian Sampling.

Changyou Chen, Ruiyi Zhang, Wenlin Wang, Bai Li, Liqun Chen

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018