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Certified Robustness of Graph Classification against Topology Attack
  with Randomized Smoothing

Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing

Global Communications Conference (GLOBECOM), 2020
12 September 2020
Zhidong Gao
Rui Hu
Yanmin Gong
    AAMLOOD
ArXiv (abs)PDFHTML

Papers citing "Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing"

13 / 13 papers shown
Reconcile Certified Robustness and Accuracy for DNN-based Smoothed Majority Vote Classifier
Reconcile Certified Robustness and Accuracy for DNN-based Smoothed Majority Vote Classifier
Gaojie Jin
Xinping Yi
Xiaowei Huang
AAML
137
1
0
30 Sep 2025
Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers
Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers
Gaojie Jin
Tianjin Huang
Ronghui Mu
Xiaowei Huang
AAML
304
0
0
21 Mar 2025
Hierarchical Randomized Smoothing
Hierarchical Randomized SmoothingNeural Information Processing Systems (NeurIPS), 2023
Yan Scholten
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
AAML
482
9
0
24 Oct 2023
Certifiably Robust Graph Contrastive Learning
Certifiably Robust Graph Contrastive LearningNeural Information Processing Systems (NeurIPS), 2023
Min Lin
Teng Xiao
Enyan Dai
Xiang Zhang
Suhang Wang
AAML
254
11
0
05 Oct 2023
Structure-Aware Robustness Certificates for Graph Classification
Structure-Aware Robustness Certificates for Graph ClassificationConference on Uncertainty in Artificial Intelligence (UAI), 2023
Pierre Osselin
Henry Kenlay
Xiaowen Dong
258
2
0
20 Jun 2023
Incremental Randomized Smoothing Certification
Incremental Randomized Smoothing CertificationInternational Conference on Learning Representations (ICLR), 2023
Shubham Ugare
Tarun Suresh
Debangshu Banerjee
Gagandeep Singh
Sasa Misailovic
AAML
250
10
0
31 May 2023
Random Smoothing Regularization in Kernel Gradient Descent Learning
Random Smoothing Regularization in Kernel Gradient Descent Learning
Liang Ding
Tianyang Hu
Jiahan Jiang
Donghao Li
Wei Cao
Xingtai Lv
232
8
0
05 May 2023
(De-)Randomized Smoothing for Decision Stump Ensembles
(De-)Randomized Smoothing for Decision Stump EnsemblesNeural Information Processing Systems (NeurIPS), 2022
Miklós Z. Horváth
Mark Niklas Muller
Marc Fischer
Martin Vechev
234
4
0
27 May 2022
Adversarial Attacks on Graph Classification via Bayesian Optimisation
Adversarial Attacks on Graph Classification via Bayesian Optimisation
Xingchen Wan
Henry Kenlay
Binxin Ru
Arno Blaas
Michael A. Osborne
Xiaowen Dong
AAML
237
15
0
04 Nov 2021
EGC2: Enhanced Graph Classification with Easy Graph Compression
EGC2: Enhanced Graph Classification with Easy Graph CompressionInformation Sciences (Inf. Sci.), 2021
Jinyin Chen
Haiyang Xiong
Haibin Zheng
Dunjie Zhang
Jian Zhang
Mingwei Jia
Yi Liu
AAML
215
19
0
16 Jul 2021
Adversarial Robustness of Probabilistic Network Embedding for Link
  Prediction
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction
Xi Chen
Bo Kang
Jefrey Lijffijt
T. D. Bie
AAML
141
2
0
05 Jul 2021
Boosting Randomized Smoothing with Variance Reduced Classifiers
Boosting Randomized Smoothing with Variance Reduced ClassifiersInternational Conference on Learning Representations (ICLR), 2021
Miklós Z. Horváth
Mark Niklas Muller
Marc Fischer
Martin Vechev
AAMLUQCV
295
55
0
13 Jun 2021
A Targeted Universal Attack on Graph Convolutional Network
A Targeted Universal Attack on Graph Convolutional NetworkNeural Processing Letters (NPL), 2020
Jiazhu Dai
Weifeng Zhu
Xiangfeng Luo
AAMLGNN
148
24
0
29 Nov 2020
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