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cs.LG2022★ 3 cited
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor
Lijun Zhang, Wei Jiang, Jinfeng Yi +1
In this paper, we investigate an online prediction strategy named as Discounted-Normal-Predictor (Kapralov and Panigrahy, 2010) for smoothed online convex optimization (SOCO), in w…
cs.LG2022★ 12 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.LG2022★ 3 cited
Can Adversarial Training Be Manipulated By Non-Robust Features?
Lue Tao, Lei Feng, Hongxin Wei +3
Adversarial training, originally designed to resist test-time adversarial examples, has shown to be promising in mitigating training-time availability attacks. This defense ability…