most citedHow to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective

12 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20223 cited

Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices

Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu +6

In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stre…

cs.LG20221 cited

Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free

Tianlong Chen, Zhenyu Zhang, Yihua Zhang +3

Trojan attacks threaten deep neural networks (DNNs) by poisoning them to behave normally on most samples, yet to produce manipulated results for inputs attached with a particular t…

cs.CV20221 cited

Grasping the Arrow of Time from the Singularity: Decoding Micromotion in Low-dimensional Latent Spaces from StyleGAN

Qiucheng Wu, Yifan Jiang, Junru Wu +5

The disentanglement of StyleGAN latent space has paved the way for realistic and controllable image editing, but does StyleGAN know anything about temporal motion, as it was only t…

cs.LG202212 cited

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective

Yimeng Zhang, Yuguang Yao, Jinghan Jia +4

The lack of adversarial robustness has been recognized as an important issue for state-of-the-art machine learning (ML) models, e.g., deep neural networks (DNNs). Thereby, robustif…

cs.LG20221 cited

Optimizer Amalgamation

Tianshu Huang, Tianlong Chen, Sijia Liu +3

Selecting an appropriate optimizer for a given problem is of major interest for researchers and practitioners. Many analytical optimizers have been proposed using a variety of theo…