Bai Li
Cited by
Cited by
Certified adversarial robustness with additive noise
B Li, C Chen, W Wang, L Carin
Advances in Neural Information Processing Systems, 9464-9474, 2019
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling
C Chen, R Zhang, W Wang, B Li, L Chen
UAI 2018, 2018
Improving Sequence-to-Sequence Learning via Optimal Transport
L Chen, Y Zhang, R Zhang, C Tao, Z Gan, H Zhang, B Li, D Shen, C Chen, ...
ICLR 2018, 2019
On Connecting Stochastic Gradient MCMC and Differential Privacy
B Li, C Chen, H Liu, L Carin
AISTATS 2019 89, 557--566, 2017
Towards understanding fast adversarial training
B Li, S Wang, S Jana, L Carin
arXiv preprint arXiv:2006.03089, 2020
Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction
Y Lu, Y Jia, J Wang, B Li, W Chai, L Carin, S Velipasalar
CVPR 2020, 2019
A privacy preserving algorithm to release sparse high-dimensional histograms
B Li, V Karwa, A Slavković, RC Steorts
Journal of Privacy and Confidentiality 8 (1), 2018
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning
W Wang, H Xu, Z Gan, B Li, G Wang, L Chen, Q Yang, W Wang, L Carin
AAAI 2020, 2019
Towards Practical Lottery Ticket Hypothesis for Adversarial Training
B Li, S Wang, Y Jia, Y Lu, Z Zhong, L Carin, S Jana
arXiv preprint arXiv:2003.05733, 2020
On Norm-Agnostic Robustness of Adversarial Training
B Li, C Chen, W Wang, L Carin
ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning, 2019
Second-order adversarial attack and certifiable robustness. arXiv
B Li, C Chen, W Wang, L Carin
Learning, 2018
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