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Boosting Adversarial Robustness using Feature Level Stochastic Smoothing

Boosting Adversarial Robustness using Feature Level Stochastic Smoothing

10 June 2023
Sravanti Addepalli
Samyak Jain
Gaurang Sriramanan
R. Venkatesh Babu
    AAML
ArXivPDFHTML

Papers citing "Boosting Adversarial Robustness using Feature Level Stochastic Smoothing"

4 / 4 papers shown
Title
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
Astha Verma
A. Subramanyam
Siddhesh Bangar
Naman Lal
R. Shah
Shiníchi Satoh
45
4
0
13 Apr 2023
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness
Ameya Joshi
Minh Pham
Minsu Cho
Leonid Boytsov
Filipe Condessa
J. Zico Kolter
Chinmay Hegde
UQCV
AAML
34
2
0
12 May 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization
  Perspective
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang
Yuguang Yao
Jinghan Jia
Jinfeng Yi
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
31
33
0
27 Mar 2022
A New Defense Against Adversarial Images: Turning a Weakness into a
  Strength
A New Defense Against Adversarial Images: Turning a Weakness into a Strength
Tao Yu
Shengyuan Hu
Chuan Guo
Wei-Lun Chao
Kilian Q. Weinberger
AAML
58
101
0
16 Oct 2019
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