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Towards Fast Computation of Certified Robustness for ReLU Networks

Towards Fast Computation of Certified Robustness for ReLU Networks

25 April 2018
Tsui-Wei Weng
Huan Zhang
Hongge Chen
Zhao-quan Song
Cho-Jui Hsieh
Duane S. Boning
Inderjit S. Dhillon
Luca Daniel
    AAML
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Papers citing "Towards Fast Computation of Certified Robustness for ReLU Networks"

50 / 118 papers shown
Title
CERT-ED: Certifiably Robust Text Classification for Edit Distance
CERT-ED: Certifiably Robust Text Classification for Edit Distance
Zhuoqun Huang
Yipeng Wang
Seunghee Shin
Benjamin I. P. Rubinstein
AAML
40
1
0
01 Aug 2024
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing
Meiyu Zhong
Ravi Tandon
36
3
0
03 Jul 2024
Probabilistic Verification of Neural Networks using Branch and Bound
Probabilistic Verification of Neural Networks using Branch and Bound
David Boetius
Stefan Leue
Tobias Sutter
42
0
0
27 May 2024
A Survey of Neural Network Robustness Assessment in Image Recognition
A Survey of Neural Network Robustness Assessment in Image Recognition
Jie Wang
Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
Junda Zhu
Jingyu Liu
AAML
30
3
0
12 Apr 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification
Trust Regions for Explanations via Black-Box Probabilistic Certification
Amit Dhurandhar
Swagatam Haldar
Dennis L. Wei
K. Ramamurthy
FAtt
21
2
0
17 Feb 2024
Set-Based Training for Neural Network Verification
Set-Based Training for Neural Network Verification
Lukas Koller
Tobias Ladner
Matthias Althoff
AAML
48
1
0
26 Jan 2024
Fast and Exact Enumeration of Deep Networks Partitions Regions
Fast and Exact Enumeration of Deep Networks Partitions Regions
Randall Balestriero
Yann LeCun
16
5
0
20 Jan 2024
Fast Certification of Vision-Language Models Using Incremental
  Randomized Smoothing
Fast Certification of Vision-Language Models Using Incremental Randomized Smoothing
Ashutosh Nirala
Ameya Joshi
Chinmay Hegde
S Sarkar
VLM
33
0
0
15 Nov 2023
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep
  Neural Networks
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks
Yang Wang
B. Dong
Ke Xu
Haiyin Piao
Yufei Ding
Baocai Yin
Xin Yang
AAML
31
3
0
10 Oct 2023
Tight Certified Robustness via Min-Max Representations of ReLU Neural
  Networks
Tight Certified Robustness via Min-Max Representations of ReLU Neural Networks
Brendon G. Anderson
Samuel Pfrommer
Somayeh Sojoudi
OOD
24
1
0
07 Oct 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Mahyar Fazlyab
Taha Entesari
Aniket Roy
Ramalingam Chellappa
AAML
16
11
0
29 Sep 2023
Uncertainty Estimation and Out-of-Distribution Detection for Deep
  Learning-Based Image Reconstruction using the Local Lipschitz
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz
D. Bhutto
Bo Zhu
J. Liu
Neha Koonjoo
H. Li
Bruce Rosen
M. Rosen
UQCV
OOD
15
2
0
12 May 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
94
32
0
29 Apr 2023
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
24
15
0
31 Jan 2023
Certified Invertibility in Neural Networks via Mixed-Integer Programming
Certified Invertibility in Neural Networks via Mixed-Integer Programming
Tianqi Cui
Tom S. Bertalan
George J. Pappas
M. Morari
Ioannis G. Kevrekidis
Mahyar Fazlyab
AAML
19
2
0
27 Jan 2023
Certified Interpretability Robustness for Class Activation Mapping
Certified Interpretability Robustness for Class Activation Mapping
Alex Gu
Tsui-Wei Weng
Pin-Yu Chen
Sijia Liu
Lucani E. Daniel
AAML
21
2
0
26 Jan 2023
Robust Explanation Constraints for Neural Networks
Robust Explanation Constraints for Neural Networks
Matthew Wicker
Juyeon Heo
Luca Costabello
Adrian Weller
FAtt
21
17
0
16 Dec 2022
veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection
  System
veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System
Guy Amir
Ziv Freund
Guy Katz
Elad Mandelbaum
Idan Refaeli
38
13
0
06 Dec 2022
Improved techniques for deterministic l2 robustness
Improved techniques for deterministic l2 robustness
Sahil Singla
S. Feizi
AAML
23
9
0
15 Nov 2022
Towards Global Neural Network Abstractions with Locally-Exact
  Reconstruction
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction
Edoardo Manino
I. Bessa
Lucas C. Cordeiro
19
1
0
21 Oct 2022
On the tightness of linear relaxation based robustness certification
  methods
On the tightness of linear relaxation based robustness certification methods
Cheng Tang
AAML
21
0
0
01 Oct 2022
Backward Reachability Analysis of Neural Feedback Loops: Techniques for
  Linear and Nonlinear Systems
Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems
Nicholas Rober
Sydney M. Katz
Chelsea Sidrane
Esen Yel
Michael Everett
Mykel J. Kochenderfer
Jonathan P. How
32
26
0
28 Sep 2022
Polynomial-Time Reachability for LTI Systems with Two-Level Lattice
  Neural Network Controllers
Polynomial-Time Reachability for LTI Systems with Two-Level Lattice Neural Network Controllers
James Ferlez
Yasser Shoukry
12
1
0
20 Sep 2022
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities:
  Robustness, Safety, and Generalizability
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability
Mengdi Xu
Zuxin Liu
Peide Huang
Wenhao Ding
Zhepeng Cen
Bo-wen Li
Ding Zhao
71
45
0
16 Sep 2022
Provably Tightest Linear Approximation for Robustness Verification of
  Sigmoid-like Neural Networks
Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks
Zhaodi Zhang
Yiting Wu
Siwen Liu
Jing Liu
Min Zhang
AAML
23
11
0
21 Aug 2022
Provable Defense Against Geometric Transformations
Provable Defense Against Geometric Transformations
Rem Yang
Jacob S. Laurel
Sasa Misailovic
Gagandeep Singh
AAML
25
15
0
22 Jul 2022
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
Ronghui Mu
Wenjie Ruan
Leandro Soriano Marcolino
Q. Ni
3DPC
24
10
0
15 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing
Yijiang Pang
Boyang Liu
Jiayu Zhou
OOD
AAML
19
1
0
11 Jul 2022
Open- and Closed-Loop Neural Network Verification using Polynomial
  Zonotopes
Open- and Closed-Loop Neural Network Verification using Polynomial Zonotopes
Niklas Kochdumper
Christian Schilling
Matthias Althoff
Stanley Bak
26
33
0
06 Jul 2022
PRoA: A Probabilistic Robustness Assessment against Functional
  Perturbations
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations
Tianle Zhang
Wenjie Ruan
J. Fieldsend
AAML
13
21
0
05 Jul 2022
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal
  Verification Perspective
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Mark Huasong Meng
Guangdong Bai
Sin Gee Teo
Zhe Hou
Yan Xiao
Yun Lin
J. Dong
AAML
21
43
0
24 Jun 2022
Riemannian data-dependent randomized smoothing for neural networks
  certification
Riemannian data-dependent randomized smoothing for neural networks certification
Pol Labarbarie
H. Hajri
M. Arnaudon
23
4
0
21 Jun 2022
The Consistency of Adversarial Training for Binary Classification
Natalie Frank
Jonathan Niles-Weed
AAML
33
5
0
18 Jun 2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical
  Analysis
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis
Raphael Ettedgui
Alexandre Araujo
Rafael Pinot
Y. Chevaleyre
Jamal Atif
AAML
32
3
0
03 Jun 2022
(De-)Randomized Smoothing for Decision Stump Ensembles
(De-)Randomized Smoothing for Decision Stump Ensembles
Miklós Z. Horváth
Mark Niklas Muller
Marc Fischer
Martin Vechev
22
3
0
27 May 2022
Verifying Neural Networks Against Backdoor Attacks
Verifying Neural Networks Against Backdoor Attacks
Long H. Pham
Jun Sun
AAML
26
5
0
14 May 2022
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
18
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
13
33
0
27 Mar 2022
Efficient Neural Network Analysis with Sum-of-Infeasibilities
Efficient Neural Network Analysis with Sum-of-Infeasibilities
Haoze Wu
Aleksandar Zeljić
Guy Katz
Clark W. Barrett
AAML
39
30
0
19 Mar 2022
COPA: Certifying Robust Policies for Offline Reinforcement Learning
  against Poisoning Attacks
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks
Fan Wu
Linyi Li
Chejian Xu
Huan Zhang
B. Kailkhura
K. Kenthapadi
Ding Zhao
Bo-wen Li
AAML
OffRL
24
34
0
16 Mar 2022
A Domain-Theoretic Framework for Robustness Analysis of Neural Networks
A Domain-Theoretic Framework for Robustness Analysis of Neural Networks
Can Zhou
R. A. Shaikh
Yiran Li
Amin Farjudian
OOD
30
4
0
01 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors
Adversarial robustness of sparse local Lipschitz predictors
Ramchandran Muthukumar
Jeremias Sulam
AAML
32
13
0
26 Feb 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural
  Networks
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks
Matan Ostrovsky
Clark W. Barrett
Guy Katz
32
26
0
06 Jan 2022
On the Impact of Hard Adversarial Instances on Overfitting in
  Adversarial Training
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
15
13
0
14 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version)
On the Existence of the Adversarial Bayes Classifier (Extended Version)
Pranjal Awasthi
Natalie Frank
M. Mohri
21
24
0
03 Dec 2021
On the Equivalence between Neural Network and Support Vector Machine
On the Equivalence between Neural Network and Support Vector Machine
Yilan Chen
Wei Huang
Lam M. Nguyen
Tsui-Wei Weng
AAML
17
18
0
11 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local
  Lipschitz Bounds
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds
Yujia Huang
Huan Zhang
Yuanyuan Shi
J Zico Kolter
Anima Anandkumar
27
76
0
02 Nov 2021
ε-weakened Robustness of Deep Neural Networks
ε-weakened Robustness of Deep Neural Networks
Pei Huang
Yuting Yang
Minghao Liu
Fuqi Jia
Feifei Ma
Jian Zhang
AAML
19
18
0
29 Oct 2021
AugMax: Adversarial Composition of Random Augmentations for Robust
  Training
AugMax: Adversarial Composition of Random Augmentations for Robust Training
Haotao Wang
Chaowei Xiao
Jean Kossaifi
Zhiding Yu
Anima Anandkumar
Zhangyang Wang
19
106
0
26 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble
Improving Adversarial Robustness for Free with Snapshot Ensemble
Yihao Wang
AAML
UQCV
9
1
0
07 Oct 2021
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