Cover Image

On Using Certified Training towards Empirical Robustness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	De Palma, Alessandro, Durand, Serge, Chihani, Zakaria, Terrier, François, Urban, Caterina
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Generalized Certified Robustness with Multi-Norm Training
by: Jiang, Enyi, et al.
Published: (2024)

Cross-Input Certified Training for Universal Perturbations
by: Xu, Changming, et al.
Published: (2024)

Expressive Losses for Verified Robustness via Convex Combinations
by: De Palma, Alessandro, et al.
Published: (2023)

Collective Certified Robustness against Graph Injection Attacks
by: Lai, Yuni, et al.
Published: (2024)

Augment then Smooth: Reconciling Differential Privacy with Certified Robustness
by: Wu, Jiapeng, et al.
Published: (2023)

Certified Causal Defense with Generalizable Robustness
by: Qiao, Yiran, et al.
Published: (2024)

Position: Certified Robustness Does Not (Yet) Imply Model Security
by: Cullen, Andrew C., et al.
Published: (2025)

Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences
by: Lyu, Saiyue, et al.
Published: (2024)

Certified Robust Accuracy of Neural Networks Are Bounded due to Bayes Errors
by: Zhang, Ruihan, et al.
Published: (2024)

A Robust Certified Machine Unlearning Method Under Distribution Shift
by: Guo, Jinduo, et al.
Published: (2026)

CAMP in the Odyssey: Provably Robust Reinforcement Learning with Certified Radius Maximization
by: Wang, Derui, et al.
Published: (2025)

Certified Robustness to Data Poisoning in Gradient-Based Training
by: Sosnin, Philip, et al.
Published: (2024)

Robust Privacy: Inference-Time Privacy through Certified Robustness
by: Jin, Jiankai, et al.
Published: (2026)

Certifiably Robust RAG against Retrieval Corruption
by: Xiang, Chong, et al.
Published: (2024)

Certified Unlearning for Neural Networks
by: Koloskova, Anastasia, et al.
Published: (2025)

Automated Alert Classification and Triage (AACT): An Intelligent System for the Prioritisation of Cybersecurity Alerts
by: Turcotte, Melissa, et al.
Published: (2025)

Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023)

Certified Robustness to Clean-Label Poisoning Using Diffusion Denoising
by: Hong, Sanghyun, et al.
Published: (2024)

CERT-ED: Certifiably Robust Text Classification for Edit Distance
by: Huang, Zhuoqun, et al.
Published: (2024)

Towards Strong Certified Defense with Universal Asymmetric Randomization
by: Hong, Hanbin, et al.
Published: (2025)

Certifiably Robust Image Watermark
by: Jiang, Zhengyuan, et al.
Published: (2024)

AdaptDel: Adaptable Deletion Rate Randomized Smoothing for Certified Robustness
by: Huang, Zhuoqun, et al.
Published: (2025)

Vulnerability-Aware Robust Multimodal Adversarial Training
by: Zhang, Junrui, et al.
Published: (2025)

Certified PEFTSmoothing: Parameter-Efficient Fine-Tuning with Randomized Smoothing
by: Fu, Chengyan, et al.
Published: (2024)

Certified Machine Unlearning via Noisy Stochastic Gradient Descent
by: Chien, Eli, et al.
Published: (2024)

A Certified Unlearning Approach without Access to Source Data
by: Basaran, Umit Yigit, et al.
Published: (2025)

Authority Backdoor: A Certifiable Backdoor Mechanism for Authoring DNNs
by: Yang, Han, et al.
Published: (2025)

PECAN: A Deterministic Certified Defense Against Backdoor Attacks
by: Zhang, Yuhao, et al.
Published: (2023)

Robust Subgraph Learning by Monitoring Early Training Representations
by: Neshatfar, Sepideh, et al.
Published: (2024)

Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning
by: Jiang, Yu, et al.
Published: (2024)

CBD: A Certified Backdoor Detector Based on Local Dominant Probability
by: Xiang, Zhen, et al.
Published: (2023)

Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks
by: Giri, Nandakrishna, et al.
Published: (2026)

Efficient Adversarial Training in LLMs with Continuous Attacks
by: Xhonneux, Sophie, et al.
Published: (2024)

Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence
by: Fu, Shaopeng, et al.
Published: (2025)

CR-UTP: Certified Robustness against Universal Text Perturbations on Large Language Models
by: Lou, Qian, et al.
Published: (2024)

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023)

Private Training & Data Generation by Clustering Embeddings
by: Zhou, Felix, et al.
Published: (2025)

Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
by: Hong, Hanbin, et al.
Published: (2023)

Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates
by: Angioni, Daniele, et al.
Published: (2024)

AuditVotes: A Framework Towards More Deployable Certified Robustness for Graph Neural Networks
by: Lai, Yuni, et al.
Published: (2025)