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Enhancing Certified Robustness via Smoothed Weighted Ensembling

Enhancing Certified Robustness via Smoothed Weighted Ensembling

19 May 2020
Chizhou Liu
Yunzhen Feng
Ranran Wang
Bin Dong
    AAML
ArXivPDFHTML

Papers citing "Enhancing Certified Robustness via Smoothed Weighted Ensembling"

6 / 6 papers shown
Title
Dynamic ensemble selection based on Deep Neural Network Uncertainty
  Estimation for Adversarial Robustness
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness
Ruoxi Qin
Linyuan Wang
Xuehui Du
Xing-yuan Chen
Binghai Yan
AAML
26
0
0
01 Aug 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
C. Hegde
UQCV
AAML
23
2
0
12 May 2022
On the Certified Robustness for Ensemble Models and Beyond
On the Certified Robustness for Ensemble Models and Beyond
Zhuolin Yang
Linyi Li
Xiaojun Xu
B. Kailkhura
Tao Xie
Bo-wen Li
AAML
23
48
0
22 Jul 2021
Adversarial Training Helps Transfer Learning via Better Representations
Adversarial Training Helps Transfer Learning via Better Representations
Zhun Deng
Linjun Zhang
Kailas Vodrahalli
Kenji Kawaguchi
James Y. Zou
GAN
36
52
0
18 Jun 2021
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
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
1