Tianhang Zheng | DeepAI

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Di Wang
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Lu Su
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∙ 05/15/2020

Towards Assessment of Randomized Mechanisms for Certifying Adversarial Robustness

As a certified defensive technique, randomized smoothing has received co...

8 Tianhang Zheng, et al. ∙

∙ 05/15/2020

Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness

As a certified defensive technique, randomized smoothing has received co...

0 Tianhang Zheng, et al. ∙

∙ 05/14/2020

Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition

Skeleton-based action recognition has attracted increasing attention due...

2 Tianhang Zheng, et al. ∙

∙ 04/26/2019

Towards Data Poisoning Attack against Knowledge Graph Embedding

Knowledge graph embedding (KGE) is a technique for learning continuous e...

0 Hengtong Zhang, et al. ∙

∙ 01/17/2019

FID: Function Modeling-based Data-Independent and Channel-Robust Physical-Layer Identification

Trusted identification is critical to secure IoT devices. However, the l...

0 Tianhang Zheng, et al. ∙

∙ 11/28/2018

Learning Saliency Maps for Adversarial Point-Cloud Generation

3D point-cloud recognition with deep neural network (DNN) has received r...

0 Tianhang Zheng, et al. ∙

∙ 10/10/2018

Is PGD-Adversarial Training Necessary? Alternative Training via a Soft-Quantization Network with Noisy-Natural Samples Only

Recent work on adversarial attack and defense suggests that PGD is a uni...

0 Tianhang Zheng, et al. ∙

∙ 08/16/2018

Distributionally Adversarial Attack

Recent work on adversarial attack has shown that Projected Gradient Desc...

0 Tianhang Zheng, et al. ∙

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