Algorithms for Adversarially Robust Deep Learning
Fuente:
arXiv
Guardado en:
| Autor principal: | Robey, Alexander |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Towards Adversarially Robust Deep Metric Learning
por: Ke, Xiaopeng
Publicado: (2025)
por: Ke, Xiaopeng
Publicado: (2025)
Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation
por: Yamabe, Shojiro, et al.
Publicado: (2024)
por: Yamabe, Shojiro, et al.
Publicado: (2024)
Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances
por: Hart, Emma, et al.
Publicado: (2024)
por: Hart, Emma, et al.
Publicado: (2024)
Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
por: Barker, Charmaine, et al.
Publicado: (2025)
por: Barker, Charmaine, et al.
Publicado: (2025)
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
por: Liu, Qianmei, et al.
Publicado: (2024)
por: Liu, Qianmei, et al.
Publicado: (2024)
SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks
por: Robey, Alexander, et al.
Publicado: (2023)
por: Robey, Alexander, et al.
Publicado: (2023)
A Dual-Agent Adversarial Framework for Robust Generalization in Deep Reinforcement Learning
por: Xie, Zhengpeng, et al.
Publicado: (2025)
por: Xie, Zhengpeng, et al.
Publicado: (2025)
Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey
por: Schott, Lucas, et al.
Publicado: (2024)
por: Schott, Lucas, et al.
Publicado: (2024)
Enhancing Adversarial Robustness of Deep Neural Networks Through Supervised Contrastive Learning
por: Wang, Longwei, et al.
Publicado: (2024)
por: Wang, Longwei, et al.
Publicado: (2024)
Exploring Adversarial Robustness of Deep State Space Models
por: Qi, Biqing, et al.
Publicado: (2024)
por: Qi, Biqing, et al.
Publicado: (2024)
Adversarial Diffusion for Robust Reinforcement Learning
por: Foffano, Daniele, et al.
Publicado: (2025)
por: Foffano, Daniele, et al.
Publicado: (2025)
Maintaining Adversarial Robustness in Continuous Learning
por: Ru, Xiaolei, et al.
Publicado: (2024)
por: Ru, Xiaolei, et al.
Publicado: (2024)
Adversarial Preference Learning for Robust LLM Alignment
por: Wang, Yuanfu, et al.
Publicado: (2025)
por: Wang, Yuanfu, et al.
Publicado: (2025)
AI Learning Algorithms: Deep Learning, Hybrid Models, and Large-Scale Model Integration
por: Golilarz, Noorbakhsh Amiri, et al.
Publicado: (2024)
por: Golilarz, Noorbakhsh Amiri, et al.
Publicado: (2024)
Jailbreaking Black Box Large Language Models in Twenty Queries
por: Chao, Patrick, et al.
Publicado: (2023)
por: Chao, Patrick, et al.
Publicado: (2023)
On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
por: Peng, Ze, et al.
Publicado: (2025)
por: Peng, Ze, et al.
Publicado: (2025)
Learning Robust Reasoning through Guided Adversarial Self-Play
por: Li, Shuozhe, et al.
Publicado: (2026)
por: Li, Shuozhe, et al.
Publicado: (2026)
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
por: Kim, Taejin, et al.
Publicado: (2023)
por: Kim, Taejin, et al.
Publicado: (2023)
Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model
por: Herremans, Siemen, et al.
Publicado: (2024)
por: Herremans, Siemen, et al.
Publicado: (2024)
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems
por: Windmann, Alexander, et al.
Publicado: (2025)
por: Windmann, Alexander, et al.
Publicado: (2025)
Adversarially Robust Decision Transformer
por: Tang, Xiaohang, et al.
Publicado: (2024)
por: Tang, Xiaohang, et al.
Publicado: (2024)
Robust off-policy Reinforcement Learning via Soft Constrained Adversary
por: Nakanishi, Kosuke, et al.
Publicado: (2024)
por: Nakanishi, Kosuke, et al.
Publicado: (2024)
Dynamic Adversarial Reinforcement Learning for Robust Multimodal Large Language Models
por: Bao, Yicheng, et al.
Publicado: (2026)
por: Bao, Yicheng, et al.
Publicado: (2026)
Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
por: Luu, Tung M., et al.
Publicado: (2024)
por: Luu, Tung M., et al.
Publicado: (2024)
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
por: Pal, Ambar, et al.
Publicado: (2023)
por: Pal, Ambar, et al.
Publicado: (2023)
How Worst-Case Are Adversarial Attacks? Linking Adversarial and Perturbation Robustness
por: Rossolini, Giulio
Publicado: (2026)
por: Rossolini, Giulio
Publicado: (2026)
Evaluating Robustness of Reinforcement Learning Algorithms for Autonomous Shipping
por: Lesy, Bavo, et al.
Publicado: (2024)
por: Lesy, Bavo, et al.
Publicado: (2024)
Robust Decision Aggregation with Adversarial Experts
por: Guo, Yongkang, et al.
Publicado: (2024)
por: Guo, Yongkang, et al.
Publicado: (2024)
Adversarial Robustness Overestimation and Instability in TRADES
por: Li, Jonathan Weiping, et al.
Publicado: (2024)
por: Li, Jonathan Weiping, et al.
Publicado: (2024)
UACER: An Uncertainty-Adaptive Critic Ensemble Framework for Robust Adversarial Reinforcement Learning
por: Wu, Jiaxi, et al.
Publicado: (2025)
por: Wu, Jiaxi, et al.
Publicado: (2025)
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
por: Wang, Longwei, et al.
Publicado: (2025)
por: Wang, Longwei, et al.
Publicado: (2025)
Efficiency Robustness of Dynamic Deep Learning Systems
por: Rathnasuriya, Ravishka, et al.
Publicado: (2025)
por: Rathnasuriya, Ravishka, et al.
Publicado: (2025)
Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering
por: Kritharakis, Emmanouil, et al.
Publicado: (2025)
por: Kritharakis, Emmanouil, et al.
Publicado: (2025)
CEAR: Certified Ensemble Adversarial Robustness in DNNs
por: Sadig, Daniel, et al.
Publicado: (2026)
por: Sadig, Daniel, et al.
Publicado: (2026)
Adversarial Robustness of VAEs across Intersectional Subgroups
por: Ramanaik, Chethan Krishnamurthy, et al.
Publicado: (2024)
por: Ramanaik, Chethan Krishnamurthy, et al.
Publicado: (2024)
ROKA: Robust Knowledge Unlearning against Adversaries
por: Shin, Jinmyeong, et al.
Publicado: (2026)
por: Shin, Jinmyeong, et al.
Publicado: (2026)
An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
por: Zhu, Jiahui, et al.
Publicado: (2025)
por: Zhu, Jiahui, et al.
Publicado: (2025)
Impact of Architectural Modifications on Deep Learning Adversarial Robustness
por: Juraev, Firuz, et al.
Publicado: (2024)
por: Juraev, Firuz, et al.
Publicado: (2024)
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
por: Cui, Canyixing, et al.
Publicado: (2026)
por: Cui, Canyixing, et al.
Publicado: (2026)
FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning
por: Tang, Minxue, et al.
Publicado: (2024)
por: Tang, Minxue, et al.
Publicado: (2024)
Ejemplares similares
-
Towards Adversarially Robust Deep Metric Learning
por: Ke, Xiaopeng
Publicado: (2025) -
Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation
por: Yamabe, Shojiro, et al.
Publicado: (2024) -
Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances
por: Hart, Emma, et al.
Publicado: (2024) -
Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
por: Barker, Charmaine, et al.
Publicado: (2025) -
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
por: Liu, Qianmei, et al.
Publicado: (2024)