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UniCR: Universally Approximated Certified Robustness via Randomized
  Smoothing

UniCR: Universally Approximated Certified Robustness via Randomized Smoothing

5 July 2022
Hanbin Hong
Binghui Wang
Yuan Hong
    AAML
ArXivPDFHTML

Papers citing "UniCR: Universally Approximated Certified Robustness via Randomized Smoothing"

5 / 5 papers shown
Title
An Eye for an Eye: Defending against Gradient-based Attacks with
  Gradients
An Eye for an Eye: Defending against Gradient-based Attacks with Gradients
Hanbin Hong
Yuan Hong
Yu Kong
AAML
19
2
0
02 Feb 2022
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
Certified Robustness to Adversarial Word Substitutions
Certified Robustness to Adversarial Word Substitutions
Robin Jia
Aditi Raghunathan
Kerem Göksel
Percy Liang
AAML
183
290
0
03 Sep 2019
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
228
1,835
0
03 Feb 2017
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
296
39,194
0
01 Sep 2014
1