102 citations · 115 across the 10 of their papers we have counts for
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cs.CR2021★ 102 cited
A Review of Adversarial Attack and Defense for Classification Methods
Yao Li, Minhao Cheng, Cho-Jui Hsieh +1
Despite the efficiency and scalability of machine learning systems, recent studies have demonstrated that many classification methods, especially deep neural networks (DNNs), are v…
stat.ML2021★ 1 cited
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms
Qin Ding, Yue Kang, Yi-Wei Liu +3
The stochastic contextual bandit problem, which models the trade-off between exploration and exploitation, has many real applications, including recommender systems, online adverti…
stat.ML2021★ 4 cited
Adversarial Examples Detection with Bayesian Neural Network
Yao Li, Tongyi Tang, Cho-Jui Hsieh +1
In this paper, we propose a new framework to detect adversarial examples motivated by the observations that random components can improve the smoothness of predictors and make it e…