ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 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
v1v2v3 (latest)

Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017
Eric Wong
J. Zico Kolter
    AAML
ArXiv (abs)PDFHTMLGithub (387★)

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

50 / 957 papers shown
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
192
1
0
08 Aug 2022
On Transfer of Adversarial Robustness from Pretraining to Downstream
  Tasks
On Transfer of Adversarial Robustness from Pretraining to Downstream TasksNeural Information Processing Systems (NeurIPS), 2022
Laura Fee Nern
Harsh Raj
Maurice Georgi
Yash Sharma
AAML
279
7
0
07 Aug 2022
Quantifying Safety of Learning-based Self-Driving Control Using
  Almost-Barrier Functions
Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier FunctionsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022
Zhizhen Qin
Tsui-Wei Weng
Sicun Gao
187
16
0
28 Jul 2022
Perception-Aware Attack: Creating Adversarial Music via
  Reverse-Engineering Human Perception
Perception-Aware Attack: Creating Adversarial Music via Reverse-Engineering Human PerceptionConference on Computer and Communications Security (CCS), 2022
Rui Duan
Zhe Qu
Shangqing Zhao
Leah Ding
Yao-Hong Liu
Zhuo Lu
AAML
158
9
0
26 Jul 2022
Certified Neural Network Watermarks with Randomized Smoothing
Certified Neural Network Watermarks with Randomized SmoothingInternational Conference on Machine Learning (ICML), 2022
Arpit Bansal
Ping Yeh-Chiang
Michael J. Curry
R. Jain
Curtis Wigington
Varun Manjunatha
John P. Dickerson
Tom Goldstein
AAML
245
58
0
16 Jul 2022
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
3DVerifier: Efficient Robustness Verification for 3D Point Cloud ModelsMachine-mediated learning (ML), 2022
Ronghui Mu
Wenjie Ruan
Leandro Soriano Marcolino
Q. Ni
3DPC
239
12
0
15 Jul 2022
Provably Adversarially Robust Nearest Prototype Classifiers
Provably Adversarially Robust Nearest Prototype ClassifiersInternational Conference on Machine Learning (ICML), 2022
Václav Voráček
Matthias Hein
AAML
224
13
0
14 Jul 2022
Certified Adversarial Robustness via Anisotropic Randomized Smoothing
Certified Adversarial Robustness via Anisotropic Randomized Smoothing
Hanbin Hong
Yuan Hong
AAML
226
6
0
12 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing
Yijiang Pang
Boyang Liu
Jiayu Zhou
OODAAML
172
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 accuracyInternational Conference on Machine Learning (ICML), 2022
R. Olivier
Bhiksha Raj
AAML
203
7
0
08 Jul 2022
UniCR: Universally Approximated Certified Robustness via Randomized
  Smoothing
UniCR: Universally Approximated Certified Robustness via Randomized SmoothingEuropean Conference on Computer Vision (ECCV), 2022
Hanbin Hong
Binghui Wang
Yuan Hong
AAML
209
15
0
05 Jul 2022
Abstraction and Refinement: Towards Scalable and Exact Verification of
  Neural Networks
Abstraction and Refinement: Towards Scalable and Exact Verification of Neural NetworksACM Transactions on Software Engineering and Methodology (TOSEM), 2022
Jiaxiang Liu
Yunhan Xing
Xiaomu Shi
Fu Song
Zhiwu Xu
Zhong Ming
178
14
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
377
19
0
29 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness EvaluationsNeural Information Processing Systems (NeurIPS), 2022
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
195
20
0
28 Jun 2022
Stability Verification of Neural Network Controllers using Mixed-Integer
  Programming
Stability Verification of Neural Network Controllers using Mixed-Integer ProgrammingIEEE Transactions on Automatic Control (TAC), 2022
Roland Schwan
Colin N. Jones
Daniel Kuhn
252
33
0
27 Jun 2022
Defending Multimodal Fusion Models against Single-Source Adversaries
Defending Multimodal Fusion Models against Single-Source AdversariesComputer Vision and Pattern Recognition (CVPR), 2021
Karren D. Yang
Wan-Yi Lin
M. Barman
Filipe Condessa
Zico Kolter
AAML
191
41
0
25 Jun 2022
On Certifying and Improving Generalization to Unseen Domains
On Certifying and Improving Generalization to Unseen Domains
Akshay Mehra
B. Kailkhura
Pin-Yu Chen
Jihun Hamm
OOD
227
5
0
24 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 PerspectiveIEEE Transactions on Dependable and Secure Computing (TDSC), 2022
Mark Huasong Meng
Guangdong Bai
Sin Gee Teo
Zhe Hou
Yan Xiao
Yun Lin
Jin Song Dong
AAML
197
62
0
24 Jun 2022
Piecewise Linear Neural Networks and Deep Learning
Piecewise Linear Neural Networks and Deep LearningNature Reviews Methods Primers (NRMP), 2022
Qinghua Tao
Li Li
Xiaolin Huang
Xiangming Xi
Shuning Wang
Johan A. K. Suykens
152
38
0
18 Jun 2022
The Consistency of Adversarial Training for Binary Classification
Natalie Frank
Jonathan Niles-Weed
AAML
237
5
0
18 Jun 2022
Double Sampling Randomized Smoothing
Double Sampling Randomized SmoothingInternational Conference on Machine Learning (ICML), 2022
Linyi Li
Jiawei Zhang
Tao Xie
Yue Liu
AAML
490
28
0
16 Jun 2022
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable RobustnessInternational Conference on Machine Learning (ICML), 2022
Tianlong Chen
Huan Zhang
Zhenyu Zhang
Shiyu Chang
Sijia Liu
Pin-Yu Chen
Zinan Lin
AAML
202
17
0
15 Jun 2022
Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by
  Out-of-Distribution Detection
Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by Out-of-Distribution Detection
Abderrahmen Amich
Ata Kaboudi
Birhanu Eshete
AAMLOODD
88
3
0
15 Jun 2022
Can pruning improve certified robustness of neural networks?
Can pruning improve certified robustness of neural networks?
Zhangheng Li
Tianlong Chen
Linyi Li
Yue Liu
Zinan Lin
AAML
233
16
0
15 Jun 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at
  Scale
Distributed Adversarial Training to Robustify Deep Neural Networks at ScaleConference on Uncertainty in Artificial Intelligence (UAI), 2022
Gaoyuan Zhang
Songtao Lu
Yihua Zhang
Xiangyi Chen
Pin-Yu Chen
Quanfu Fan
Lee Martie
L. Horesh
Min-Fong Hong
Sijia Liu
OOD
267
14
0
13 Jun 2022
GSmooth: Certified Robustness against Semantic Transformations via
  Generalized Randomized Smoothing
GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized SmoothingInternational Conference on Machine Learning (ICML), 2022
Zhongkai Hao
Chengyang Ying
Yinpeng Dong
Hang Su
Jun Zhu
Jian Song
AAML
158
25
0
09 Jun 2022
Toward Certified Robustness Against Real-World Distribution Shifts
Toward Certified Robustness Against Real-World Distribution Shifts
Haoze Wu
Teruhiro Tagomori
Avi Schwarzschild
Fengjun Yang
Nikolai Matni
George Pappas
Hamed Hassani
C. Păsăreanu
Clark W. Barrett
AAMLOOD
219
23
0
08 Jun 2022
Chordal Sparsity for SDP-based Neural Network Verification
Chordal Sparsity for SDP-based Neural Network Verification
Anton Xue
Lars Lindemann
Rajeev Alur
247
4
0
07 Jun 2022
Building Robust Ensembles via Margin Boosting
Building Robust Ensembles via Margin BoostingInternational Conference on Machine Learning (ICML), 2022
Dinghuai Zhang
Hongyang R. Zhang
Aaron Courville
Yoshua Bengio
Pradeep Ravikumar
A. Suggala
AAMLUQCV
172
17
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
AAMLFedML
256
10
0
06 Jun 2022
Fast Adversarial Training with Adaptive Step Size
Fast Adversarial Training with Adaptive Step SizeIEEE Transactions on Image Processing (IEEE TIP), 2022
Zhichao Huang
Yanbo Fan
Chen Liu
Weizhong Zhang
Yong Zhang
Mathieu Salzmann
Sabine Süsstrunk
Jue Wang
AAML
157
43
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
161
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 NetworksConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2022
Kiarash Mohammadi
Aishwarya Sivaraman
G. Farnadi
266
9
0
01 Jun 2022
On the Perils of Cascading Robust Classifiers
On the Perils of Cascading Robust ClassifiersInternational Conference on Learning Representations (ICLR), 2022
Ravi Mangal
Zifan Wang
Chi Zhang
Klas Leino
C. Păsăreanu
Matt Fredrikson
AAML
239
1
0
01 Jun 2022
Optimizing Objective Functions from Trained ReLU Neural Networks via
  Sampling
Optimizing Objective Functions from Trained ReLU Neural Networks via Sampling
Georgia Perakis
Asterios Tsiourvas
216
15
0
27 May 2022
(De-)Randomized Smoothing for Decision Stump Ensembles
(De-)Randomized Smoothing for Decision Stump EnsemblesNeural Information Processing Systems (NeurIPS), 2022
Miklós Z. Horváth
Mark Niklas Muller
Marc Fischer
Martin Vechev
235
4
0
27 May 2022
Certified Robustness Against Natural Language Attacks by Causal
  Intervention
Certified Robustness Against Natural Language Attacks by Causal InterventionInternational Conference on Machine Learning (ICML), 2022
Haiteng Zhao
Chang Ma
Xinshuai Dong
Anh Tuan Luu
Zhi-Hong Deng
Hanwang Zhang
AAML
360
42
0
24 May 2022
Post-breach Recovery: Protection against White-box Adversarial Examples
  for Leaked DNN Models
Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN ModelsConference on Computer and Communications Security (CCS), 2022
Shawn Shan
Wen-Luan Ding
Emily Wenger
Haitao Zheng
Ben Y. Zhao
AAML
216
15
0
21 May 2022
Getting a-Round Guarantees: Floating-Point Attacks on Certified
  Robustness
Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness
Jiankai Jin
O. Ohrimenko
Benjamin I. P. Rubinstein
AAML
262
4
0
20 May 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks
CertiFair: A Framework for Certified Global Fairness of Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2022
Haitham Khedr
Yasser Shoukry
FedML
177
26
0
20 May 2022
Verifying Neural Networks Against Backdoor Attacks
Verifying Neural Networks Against Backdoor AttacksNational Foundation for Science and Technology Development Conference on Information and Computer Science (TDICS), 2022
Long H. Pham
Jun Sun
AAML
152
6
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
Chinmay Hegde
UQCVAAML
202
2
0
12 May 2022
Do You Think You Can Hold Me? The Real Challenge of Problem-Space
  Evasion Attacks
Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks
Harel Berger
A. Dvir
Chen Hajaj
Rony Ronen
AAML
207
3
0
09 May 2022
Adversarial Training for High-Stakes Reliability
Adversarial Training for High-Stakes ReliabilityNeural Information Processing Systems (NeurIPS), 2022
Daniel M. Ziegler
Seraphina Nix
Lawrence Chan
Tim Bauman
Peter Schmidt-Nielsen
...
Noa Nabeshima
Benjamin Weinstein-Raun
D. Haas
Buck Shlegeris
Nate Thomas
AAML
554
71
0
03 May 2022
Complete Verification via Multi-Neuron Relaxation Guided
  Branch-and-Bound
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-BoundInternational Conference on Learning Representations (ICLR), 2022
Claudio Ferrari
Mark Niklas Muller
Nikola Jovanović
Martin Vechev
232
101
0
30 Apr 2022
Robust stabilization of polytopic systems via fast and reliable neural
  network-based approximations
Robust stabilization of polytopic systems via fast and reliable neural network-based approximations
F. Fabiani
Paul Goulart
143
7
0
27 Apr 2022
How Sampling Impacts the Robustness of Stochastic Neural Networks
How Sampling Impacts the Robustness of Stochastic Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Sina Daubener
Asja Fischer
SILMAAML
218
1
0
22 Apr 2022
Sardino: Ultra-Fast Dynamic Ensemble for Secure Visual Sensing at Mobile
  Edge
Sardino: Ultra-Fast Dynamic Ensemble for Secure Visual Sensing at Mobile EdgeEuropean Conference/Workshop on Wireless Sensor Networks (EWSN), 2022
Qun Song
Zhenyu Yan
W. Luo
Rui Tan
AAML
249
5
0
18 Apr 2022
Planting Undetectable Backdoors in Machine Learning Models
Planting Undetectable Backdoors in Machine Learning ModelsIEEE Annual Symposium on Foundations of Computer Science (FOCS), 2022
S. Goldwasser
Michael P. Kim
Vinod Vaikuntanathan
Or Zamir
AAML
185
84
0
14 Apr 2022
Synthesizing Adversarial Visual Scenarios for Model-Based Robotic
  Control
Synthesizing Adversarial Visual Scenarios for Model-Based Robotic ControlConference on Robot Learning (CoRL), 2022
Shubhankar Agarwal
Sandeep Chinchali
AAML
311
5
0
13 Apr 2022
Previous
123...567...181920
Next