Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2002.08118
Cited By
v1
v2
v3
v4
v5 (latest)
Randomized Smoothing of All Shapes and Sizes
International Conference on Machine Learning (ICML), 2020
19 February 2020
Greg Yang
Tony Duan
J. E. Hu
Hadi Salman
Ilya P. Razenshteyn
Jungshian Li
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
Github (52★)
Papers citing
"Randomized Smoothing of All Shapes and Sizes"
50 / 119 papers shown
Dual Randomized Smoothing: Beyond Global Noise Variance
Chenhao Sun
Yuhao Mao
Martin Vechev
AAML
331
1
0
01 Dec 2025
Towards Strong Certified Defense with Universal Asymmetric Randomization
Hanbin Hong
Ashish Kundu
Ali Payani
Binghui Wang
Yuan Hong
AAML
195
0
0
22 Oct 2025
Randomized Smoothing Meets Vision-Language Models
Emmanouil Seferis
Changshun Wu
Stefanos D. Kollias
Saddek Bensalem
Chih-Hong Cheng
AAML
151
0
0
19 Sep 2025
One Sample is Enough to Make Conformal Prediction Robust
Soroush H. Zargarbashi
Mohammad Sadegh Akhondzadeh
Aleksandar Bojchevski
290
3
0
19 Jun 2025
Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew C. Cullen
Paul Montague
S. Erfani
Benjamin I. P. Rubinstein
300
0
0
16 Jun 2025
Towards Better Generalization via Distributional Input Projection Network
Yifan Hao
Yanxin Lu
Xinwei Shen
Tong Zhang
Tong Zhang
301
1
0
05 Jun 2025
Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise
Lucas Tecot
Di Luo
Cho-Jui Hsieh
232
0
0
24 May 2025
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
Bo-Han Lai
Pin-Han Huang
Bo-Han Kung
Shang-Tse Chen
357
4
0
21 May 2025
Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers
Gaojie Jin
Tianjin Huang
Ronghui Mu
Xiaowei Huang
AAML
393
0
0
21 Mar 2025
CeTAD: Towards Certified Toxicity-Aware Distance in Vision Language Models
Xiangyu Yin
Jiaxu Liu
Zhen Chen
Jinwei Hu
Yi Dong
Xiaowei Huang
Wenjie Ruan
AAML
367
0
0
08 Mar 2025
ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs
Yuchen Yang
Shubham Ugare
Yifan Zhao
Gagandeep Singh
Sasa Misailovic
MQ
391
2
0
31 Oct 2024
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness
Vaclav Voracek
AAML
386
6
0
25 Jun 2024
Robust width: A lightweight and certifiable adversarial defense
Jonathan Peck
Bart Goossens
AAML
240
3
0
24 May 2024
RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothing
Aref Miri Rekavandi
Olga Ohrimenko
Benjamin I. P. Rubinstein
AAML
249
4
0
14 May 2024
Certification of Speaker Recognition Models to Additive Perturbations
Dmitrii Korzh
Elvir Karimov
Mikhail Aleksandrovich Pautov
Oleg Y. Rogov
Ivan Oseledets
351
8
0
29 Apr 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
Devansh Bhardwaj
Kshitiz Kaushik
Sarthak Gupta
AAML
377
0
0
12 Feb 2024
PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks
Ping Guo
Xiang Li
Zhiyuan Yang
Xi Lin
Qingchuan Zhao
Qingfu Zhang
AAML
398
4
0
19 Jan 2024
GSE: Group-wise Sparse and Explainable Adversarial Attacks
International Conference on Learning Representations (ICLR), 2023
Shpresim Sadiku
Moritz Wagner
Sebastian Pokutta
AAML
439
5
0
29 Nov 2023
Fast Certification of Vision-Language Models Using Incremental Randomized Smoothing
Ashutosh Nirala
Ameya Joshi
Chinmay Hegde
S Sarkar
VLM
421
2
0
15 Nov 2023
Multi-scale Diffusion Denoised Smoothing
Neural Information Processing Systems (NeurIPS), 2023
Jongheon Jeong
Jinwoo Shin
DiffM
395
14
0
25 Oct 2023
Is Certifying
ℓ
p
\ell_p
ℓ
p
Robustness Still Worthwhile?
Ravi Mangal
Klas Leino
Zifan Wang
Kai Hu
Weicheng Yu
Corina S. Pasareanu
Anupam Datta
Matt Fredrikson
AAML
OOD
305
1
0
13 Oct 2023
Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
Yuan Xin
Dingfan Chen
Michael Backes
Xiao Zhang
AAML
343
0
0
12 Oct 2023
SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks
Avi Schwarzschild
Eric Wong
Hamed Hassani
George J. Pappas
AAML
624
433
0
05 Oct 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
Neural Information Processing Systems (NeurIPS), 2023
Ambar Pal
Huaijin Hao
Rene Vidal
327
11
0
28 Sep 2023
Improving Viewpoint Robustness for Visual Recognition via Adversarial Training
Shouwei Ruan
Yinpeng Dong
Han Su
Jianteng Peng
Ning Chen
Xingxing Wei
215
8
0
21 Jul 2023
Stability Guarantees for Feature Attributions with Multiplicative Smoothing
Neural Information Processing Systems (NeurIPS), 2023
Anton Xue
Rajeev Alur
Eric Wong
393
16
0
12 Jul 2023
[Re] Double Sampling Randomized Smoothing
A. Gupta
Sarthak Gupta
Abhay Kumar
Harsh Dugar
AAML
178
0
0
27 Jun 2023
On Achieving Optimal Adversarial Test Error
International Conference on Learning Representations (ICLR), 2023
Justin D. Li
Matus Telgarsky
AAML
306
3
0
13 Jun 2023
Incremental Randomized Smoothing Certification
International Conference on Learning Representations (ICLR), 2023
Shubham Ugare
Tarun Suresh
Debangshu Banerjee
Gagandeep Singh
Sasa Misailovic
AAML
391
11
0
31 May 2023
Understanding Noise-Augmented Training for Randomized Smoothing
Ambar Pal
Jeremias Sulam
AAML
456
8
0
08 May 2023
Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
Conference on Computer and Communications Security (CCS), 2023
Hanbin Hong
Xinyu Zhang
Binghui Wang
Zhongjie Ba
Yuan Hong
AAML
309
6
0
10 Apr 2023
A Certified Radius-Guided Attack Framework to Image Segmentation Models
European Symposium on Security and Privacy (Euro S&P), 2023
Wenjie Qu
Youqi Li
Binghui Wang
AAML
275
5
0
05 Apr 2023
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection
Nicola Franco
Daniel Korth
J. Lorenz
Karsten Roscher
Stephan Guennemann
234
6
0
27 Mar 2023
Turning Strengths into Weaknesses: A Certified Robustness Inspired Attack Framework against Graph Neural Networks
Computer Vision and Pattern Recognition (CVPR), 2023
Binghui Wang
Meng Pang
Yun Dong
AAML
233
18
0
10 Mar 2023
A Unified Algebraic Perspective on Lipschitz Neural Networks
International Conference on Learning Representations (ICLR), 2023
Alexandre Araujo
Aaron J. Havens
Blaise Delattre
A. Allauzen
Bin Hu
AAML
307
68
0
06 Mar 2023
Run-Off Election: Improved Provable Defense against Data Poisoning Attacks
International Conference on Machine Learning (ICML), 2023
Keivan Rezaei
Kiarash Banihashem
Atoosa Malemir Chegini
Soheil Feizi
AAML
526
21
0
05 Feb 2023
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Neural Information Processing Systems (NeurIPS), 2023
Samuel Pfrommer
Brendon G. Anderson
Julien Piet
Somayeh Sojoudi
AAML
274
9
0
03 Feb 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations
International Conference on Machine Learning (ICML), 2023
Hassan Dbouk
Naresh R Shanbhag
AAML
398
8
0
02 Feb 2023
Towards Large Certified Radius in Randomized Smoothing using Quasiconcave Optimization
AAAI Conference on Artificial Intelligence (AAAI), 2023
Bo-Han Kung
Shang-Tse Chen
AAML
255
1
0
01 Feb 2023
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
Neural Information Processing Systems (NeurIPS), 2023
Zhuoqun Huang
Neil G. Marchant
Keane Lucas
Lujo Bauer
O. Ohrimenko
Benjamin I. P. Rubinstein
AAML
479
20
0
31 Jan 2023
Confidence-aware Training of Smoothed Classifiers for Certified Robustness
AAAI Conference on Artificial Intelligence (AAAI), 2022
Jongheon Jeong
Seojin Kim
Jinwoo Shin
AAML
448
11
0
18 Dec 2022
Private and Reliable Neural Network Inference
Conference on Computer and Communications Security (CCS), 2022
Nikola Jovanović
Marc Fischer
Samuel Steffen
Martin Vechev
303
22
0
27 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer
Neural Information Processing Systems (NeurIPS), 2022
Pratik Vaishnavi
Kevin Eykholt
Amir Rahmati
290
8
0
25 Oct 2022
Adversarial Pretraining of Self-Supervised Deep Networks: Past, Present and Future
Guo-Jun Qi
M. Shah
SSL
185
9
0
23 Oct 2022
Certified Training: Small Boxes are All You Need
International Conference on Learning Representations (ICLR), 2022
Mark Niklas Muller
Franziska Eckert
Marc Fischer
Martin Vechev
AAML
353
69
0
10 Oct 2022
Denoising Masked AutoEncoders Help Robust Classification
International Conference on Learning Representations (ICLR), 2022
Quanlin Wu
Hang Ye
Yuntian Gu
Huishuai Zhang
Liwei Wang
Di He
456
27
0
10 Oct 2022
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective
Neural Information Processing Systems (NeurIPS), 2022
Bohang Zhang
Du Jiang
Di He
Liwei Wang
OOD
470
82
0
04 Oct 2022
CARE: Certifiably Robust Learning with Reasoning via Variational Inference
Jiawei Zhang
Linyi Li
Ce Zhang
Yue Liu
AAML
OOD
445
12
0
12 Sep 2022
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models
Brendon G. Anderson
Tanmay Gautam
Somayeh Sojoudi
OOD
348
2
0
15 Aug 2022
Certified Adversarial Robustness via Anisotropic Randomized Smoothing
Hanbin Hong
Yuan Hong
AAML
326
7
0
12 Jul 2022
1
2
3
Next
Page 1 of 3
![[Re] Double Sampling Randomized Smoothing](https://cdn.parameterlab.de/resized-images/aHR0cHM6Ly9jZG4ucGFyYW1ldGVybGFiLmRlL3BhcGVycy8yMzA2LjE1MjIxL3BhZ2VzL3BhZ2UtMS1xODBkMzAwLmpwZw?w=256&q=75&f=webp)
