ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1711.00851
  4. Cited By
Provable defenses against adversarial examples via the convex outer
  adversarial polytope

Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017
Eric Wong
J. Zico Kolter
    AAML
ArXivPDFHTML

Papers citing "Provable defenses against adversarial examples via the convex outer adversarial polytope"

50 / 380 papers shown
Title
A Comprehensive Study on Robustness of Image Classification Models:
  Benchmarking and Rethinking
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking
Chang-Shu Liu
Yinpeng Dong
Wenzhao Xiang
Xiaohu Yang
Hang Su
Junyi Zhu
YueFeng Chen
Yuan He
H. Xue
Shibao Zheng
OOD
VLM
AAML
33
74
0
28 Feb 2023
Less is More: Data Pruning for Faster Adversarial Training
Less is More: Data Pruning for Faster Adversarial Training
Yize Li
Pu Zhao
X. Lin
B. Kailkhura
Ryan Goldh
AAML
15
9
0
23 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features
  and Neural Tangent Kernels
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels
Simone Bombari
Shayan Kiyani
Marco Mondelli
AAML
46
10
0
03 Feb 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
32
15
0
31 Jan 2023
Vertex-based reachability analysis for verifying ReLU deep neural
  networks
Vertex-based reachability analysis for verifying ReLU deep neural networks
João G. Zago
E. Camponogara
Eric A. Antonelo
AAML
29
2
0
27 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
27
2
0
27 Jan 2023
A Robust Optimisation Perspective on Counterexample-Guided Repair of
  Neural Networks
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
David Boetius
Stefan Leue
Tobias Sutter
33
4
0
26 Jan 2023
Interval Reachability of Nonlinear Dynamical Systems with Neural Network
  Controllers
Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers
Saber Jafarpour
Akash Harapanahalli
Samuel Coogan
39
10
0
19 Jan 2023
REaaS: Enabling Adversarially Robust Downstream Classifiers via Robust
  Encoder as a Service
REaaS: Enabling Adversarially Robust Downstream Classifiers via Robust Encoder as a Service
Wenjie Qu
Jinyuan Jia
Neil Zhenqiang Gong
SILM
AAML
34
4
0
07 Jan 2023
Confidence-aware Training of Smoothed Classifiers for Certified
  Robustness
Confidence-aware Training of Smoothed Classifiers for Certified Robustness
Jongheon Jeong
Seojin Kim
Jinwoo Shin
AAML
21
7
0
18 Dec 2022
Probabilistic Verification of ReLU Neural Networks via Characteristic
  Functions
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions
Joshua Pilipovsky
Vignesh Sivaramakrishnan
Meeko Oishi
Panagiotis Tsiotras
37
5
0
03 Dec 2022
Invariance-Aware Randomized Smoothing Certificates
Invariance-Aware Randomized Smoothing Certificates
Jan Schuchardt
Stephan Günnemann
AAML
28
5
0
25 Nov 2022
Understanding the Vulnerability of Skeleton-based Human Activity
  Recognition via Black-box Attack
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
Yunfeng Diao
He Wang
Tianjia Shao
Yong-Liang Yang
Kun Zhou
David C. Hogg
Meng Wang
AAML
42
7
0
21 Nov 2022
Towards Robust Dataset Learning
Towards Robust Dataset Learning
Yihan Wu
Xinda Li
Florian Kerschbaum
Heng Huang
Hongyang R. Zhang
DD
OOD
49
10
0
19 Nov 2022
Improved techniques for deterministic l2 robustness
Improved techniques for deterministic l2 robustness
Sahil Singla
S. Feizi
AAML
23
9
0
15 Nov 2022
Impact of Adversarial Training on Robustness and Generalizability of
  Language Models
Impact of Adversarial Training on Robustness and Generalizability of Language Models
Enes Altinisik
Hassan Sajjad
Husrev Taha Sencar
Safa Messaoud
Sanjay Chawla
AAML
24
8
0
10 Nov 2022
Private and Reliable Neural Network Inference
Private and Reliable Neural Network Inference
Nikola Jovanović
Marc Fischer
Samuel Steffen
Martin Vechev
22
14
0
27 Oct 2022
Adversarial Purification with the Manifold Hypothesis
Adversarial Purification with the Manifold Hypothesis
Zhaoyuan Yang
Zhiwei Xu
Jing Zhang
Richard I. Hartley
Peter Tu
AAML
24
5
0
26 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer
Accelerating Certified Robustness Training via Knowledge Transfer
Pratik Vaishnavi
Kevin Eykholt
Amir Rahmati
24
7
0
25 Oct 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz
Tsui-Wei Weng
Gal Mishne
OOD
35
4
0
20 Oct 2022
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers
Gaurav Kumar Nayak
Ruchit Rawal
Anirban Chakraborty
19
3
0
17 Oct 2022
Visual Prompting for Adversarial Robustness
Visual Prompting for Adversarial Robustness
Aochuan Chen
P. Lorenz
Yuguang Yao
Pin-Yu Chen
Sijia Liu
VLM
VPVLM
40
32
0
12 Oct 2022
Efficient Adversarial Training without Attacking: Worst-Case-Aware
  Robust Reinforcement Learning
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning
Yongyuan Liang
Yanchao Sun
Ruijie Zheng
Furong Huang
OOD
AAML
OffRL
28
47
0
12 Oct 2022
Certified Training: Small Boxes are All You Need
Certified Training: Small Boxes are All You Need
Mark Niklas Muller
Franziska Eckert
Marc Fischer
Martin Vechev
AAML
39
45
0
10 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
44
0
0
01 Oct 2022
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters
  Substitution
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters Substitution
Ming-Kuai Zhou
Xiaobing Pei
AAML
16
0
0
31 Aug 2022
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries
Dongbin Na
Sangwoo Ji
Jong Kim
AAML
35
17
0
24 Aug 2022
A Novel Plug-and-Play Approach for Adversarially Robust Generalization
A Novel Plug-and-Play Approach for Adversarially Robust Generalization
Deepak Maurya
Adarsh Barik
Jean Honorio
OOD
AAML
43
0
0
19 Aug 2022
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate
  Convolutional Neural Network Architecture From Truth Tables
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables
Adrien Benamira
Tristan Guérand
Thomas Peyrin
Trevor Yap
Bryan Hooi
40
1
0
18 Aug 2022
Robust Training and Verification of Implicit Neural Networks: A
  Non-Euclidean Contractive Approach
Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach
Saber Jafarpour
A. Davydov
Matthew Abate
Francesco Bullo
Samuel Coogan
13
1
0
08 Aug 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
32
10
0
15 Jul 2022
Provably Adversarially Robust Nearest Prototype Classifiers
Provably Adversarially Robust Nearest Prototype Classifiers
Václav Voráček
Matthias Hein
AAML
20
11
0
14 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing
Yijiang Pang
Boyang Liu
Jiayu Zhou
OOD
AAML
19
1
0
11 Jul 2022
How many perturbations break this model? Evaluating robustness beyond
  adversarial accuracy
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy
R. Olivier
Bhiksha Raj
AAML
34
5
0
08 Jul 2022
Abstraction and Refinement: Towards Scalable and Exact Verification of
  Neural Networks
Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks
Jiaxiang Liu
Yunhan Xing
Xiaomu Shi
Fu Song
Zhiwu Xu
Zhong Ming
24
10
0
02 Jul 2022
IBP Regularization for Verified Adversarial Robustness via
  Branch-and-Bound
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound
Alessandro De Palma
Rudy Bunel
Krishnamurthy Dvijotham
M. P. Kumar
Robert Stanforth
AAML
48
17
0
29 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
36
16
0
28 Jun 2022
Stability Verification of Neural Network Controllers using Mixed-Integer
  Programming
Stability Verification of Neural Network Controllers using Mixed-Integer Programming
Roland Schwan
Colin N. Jones
Daniel Kuhn
35
24
0
27 Jun 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
Jin Song Dong
AAML
32
43
0
24 Jun 2022
The Consistency of Adversarial Training for Binary Classification
Natalie Frank
Jonathan Niles-Weed
AAML
43
5
0
18 Jun 2022
Double Sampling Randomized Smoothing
Double Sampling Randomized Smoothing
Linyi Li
Jiawei Zhang
Tao Xie
Bo-wen Li
AAML
17
23
0
16 Jun 2022
Can pruning improve certified robustness of neural networks?
Can pruning improve certified robustness of neural networks?
Zhangheng Li
Tianlong Chen
Linyi Li
Bo-wen Li
Zhangyang Wang
AAML
13
11
0
15 Jun 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at
  Scale
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Gaoyuan Zhang
Songtao Lu
Yihua Zhang
Xiangyi Chen
Pin-Yu Chen
Quanfu Fan
Lee Martie
L. Horesh
Min-Fong Hong
Sijia Liu
OOD
30
12
0
13 Jun 2022
Building Robust Ensembles via Margin Boosting
Building Robust Ensembles via Margin Boosting
Dinghuai Zhang
Hongyang R. Zhang
Aaron Courville
Yoshua Bengio
Pradeep Ravikumar
A. Suggala
AAML
UQCV
48
15
0
07 Jun 2022
Certified Robustness in Federated Learning
Certified Robustness in Federated Learning
Motasem Alfarra
Juan C. Pérez
Egor Shulgin
Peter Richtárik
Guohao Li
AAML
FedML
23
7
0
06 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
34
3
0
03 Jun 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms
  for Neural Networks
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks
Kiarash Mohammadi
Aishwarya Sivaraman
G. Farnadi
25
5
0
01 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
30
3
0
27 May 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks
CertiFair: A Framework for Certified Global Fairness of Neural Networks
Haitham Khedr
Yasser Shoukry
FedML
26
20
0
20 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
Previous
12345678
Next