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Almost Tight L0-norm Certified Robustness of Top-k Predictions against
  Adversarial Perturbations

Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations

15 November 2020
Jinyuan Jia
Binghui Wang
Xiaoyu Cao
Hongbin Liu
Neil Zhenqiang Gong
ArXivPDFHTML

Papers citing "Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations"

5 / 5 papers shown
Title
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers
  via Randomized Deletion
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
Zhuoqun Huang
Neil G. Marchant
Keane Lucas
Lujo Bauer
O. Ohrimenko
Benjamin I. P. Rubinstein
AAML
27
15
0
31 Jan 2023
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks
  against Phishing Website Detectors using Machine Learning
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning
Ying Yuan
Giovanni Apruzzese
Mauro Conti
AAML
23
19
0
24 Oct 2022
PatchCleanser: Certifiably Robust Defense against Adversarial Patches
  for Any Image Classifier
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier
Chong Xiang
Saeed Mahloujifar
Prateek Mittal
VLM
AAML
24
73
0
20 Aug 2021
Certified Robustness of Community Detection against Adversarial
  Structural Perturbation via Randomized Smoothing
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing
Jinyuan Jia
Binghui Wang
Xiaoyu Cao
Neil Zhenqiang Gong
AAML
83
83
0
09 Feb 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
231
1,837
0
03 Feb 2017
1