174 citations · 313 across the 26 of their papers we have counts for
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Certified Robustness of Nearest Neighbors against Data Poisoning and Backdoor Attacks
Jinyuan Jia, Yupei Liu, Xiaoyu Cao +1
Data poisoning attacks and backdoor attacks aim to corrupt a machine learning classifier via modifying, adding, and/or removing some carefully selected training examples, such that…
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations
Jinyuan Jia, Binghui Wang, Xiaoyu Cao +2
Top-k predictions are used in many real-world applications such as machine learning as a service, recommender systems, and web searches. -norm adversarial perturbation char…
Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation
Binghui Wang, Jinyuan Jia, Xiaoyu Cao +1
Graph neural networks (GNNs) have recently gained much attention for node and graph classification tasks on graph-structured data. However, multiple recent works showed that an att…
Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks
Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong
In a \emph{data poisoning attack}, an attacker modifies, deletes, and/or inserts some training examples to corrupt the learnt machine learning model. \emph{Bootstrap Aggregating (b…
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing
Jinyuan Jia, Binghui Wang, Xiaoyu Cao +1
Community detection plays a key role in understanding graph structure. However, several recent studies showed that community detection is vulnerable to adversarial structural pertu…