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On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples
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On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples

Richard Y. Zhang
    AAML
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Papers citing "On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples"

13 / 13 papers shown
Title
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation
Ben Batten
Yang Zheng
Alessandro De Palma
Panagiotis Kouvaros
A. Lomuscio
AAML
74
1
0
23 Aug 2024
Convex Relaxation for Solving Large-Margin Classifiers in Hyperbolic Space
Convex Relaxation for Solving Large-Margin Classifiers in Hyperbolic Space
Sheng Yang
Peihan Liu
Cengiz Pehlevan
81
0
0
27 May 2024
Local Lipschitz Constant Computation of ReLU-FNNs: Upper Bound Computation with Exactness Verification
Local Lipschitz Constant Computation of ReLU-FNNs: Upper Bound Computation with Exactness Verification
Y. Ebihara
Xin Dai
Victor Magron
D. Peaucelle
Sophie Tarbouriech
25
5
0
17 Oct 2023
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
160
37
0
29 Apr 2023
Efficient Symbolic Reasoning for Neural-Network Verification
Efficient Symbolic Reasoning for Neural-Network Verification
Zi Wang
S. Jha
Krishnamurthy Dvijotham
Dvijotham
AAMLNAI
94
2
0
23 Mar 2023
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
Hong-Ming Chiu
Richard Y. Zhang
AAML
76
3
0
30 Nov 2022
On the tightness of linear relaxation based robustness certification methods
On the tightness of linear relaxation based robustness certification methods
Cheng Tang
AAML
79
0
0
01 Oct 2022
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models
Brendon G. Anderson
Tanmay Gautam
Somayeh Sojoudi
OOD
53
2
0
15 Aug 2022
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming
Robin Brown
Edward Schmerling
Navid Azizan
Marco Pavone
AAML
73
17
0
06 Mar 2022
Advances in adversarial attacks and defenses in computer vision: A survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Mian
Navid Kardan
M. Shah
AAML
162
241
0
01 Aug 2021
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks
Kendra Albert
Maggie K. Delano
B. Kulynych
Ramnath Kumar
AAML
133
5
0
11 Jul 2021
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
Brendon G. Anderson
Ziye Ma
Jingqi Li
Somayeh Sojoudi
128
1
0
22 Jan 2021
A Sequential Framework Towards an Exact SDP Verification of Neural Networks
A Sequential Framework Towards an Exact SDP Verification of Neural Networks
Ziye Ma
Somayeh Sojoudi
57
8
0
16 Oct 2020