Imagen de Portada

Optimizing the Adversarial Perturbation with a Momentum-based Adaptive Matrix

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tao, Wei, Long, Sheng, Liu, Xin, Li, Wei, Tao, Qing
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Score-based Generative Models with Adaptive Momentum
por: Wen, Ziqing, et al.
Publicado: (2024)

The Power of Decaying Steps: Enhancing Attack Stability and Transferability for Sign-based Optimizers
por: Tao, Wei, et al.
Publicado: (2026)

Distributed Learning with Adversarial Gradient Perturbations
por: Sangsiri, Nawapon, et al.
Publicado: (2026)

Variational Schrödinger Momentum Diffusion
por: Rojas, Kevin, et al.
Publicado: (2025)

Democratic Training Against Universal Adversarial Perturbations
por: Sun, Bing, et al.
Publicado: (2025)

Quantitative Convergences of Lie Group Momentum Optimizers
por: Kong, Lingkai, et al.
Publicado: (2024)

RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
por: Deng, Shenyang, et al.
Publicado: (2026)

Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum
por: Haque, Nashrah, et al.
Publicado: (2024)

Contrasting Adversarial Perturbations: The Space of Harmless Perturbations
por: Chen, Lu, et al.
Publicado: (2024)

Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
por: Pan, Xiaokang, et al.
Publicado: (2024)

Alada: Alternating Adaptation of Momentum Method for Memory-Efficient Matrix Optimization
por: He, Xiaoyu, et al.
Publicado: (2025)

DP-Muon: Differentially Private Optimization via Matrix-Orthogonalized Momentum
por: Kim, Jihwan, et al.
Publicado: (2026)

Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
por: Liu, Qianmei, et al.
Publicado: (2024)

Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation
por: Zhang, Lilin, et al.
Publicado: (2026)

Adversarial Bandit Optimization with Globally Bounded Perturbations to Linear Losses
por: Cheng, Zhuoyu, et al.
Publicado: (2026)

Constrained Adversarial Perturbation
por: Nishad, Virendra, et al.
Publicado: (2025)

Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
por: Li, Bo, et al.
Publicado: (2025)

Boosting Adversarial Transferability via Residual Perturbation Attack
por: Peng, Jinjia, et al.
Publicado: (2025)

Gradient Perturbation: Learning to Perturb Gradients for Adaptive Training
por: Li, Hua
Publicado: (2026)

Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
por: Zheng, Rui, et al.
Publicado: (2024)

Momentum Approximation in Asynchronous Private Federated Learning
por: Yu, Tao, et al.
Publicado: (2024)

Adaptive Optimization via Momentum on Variance-Normalized Gradients
por: Patitucci, Francisco, et al.
Publicado: (2026)

AdamFLIP: Adaptive Momentum Feedback Linearization Optimization for Hard Constrained PINN Training
por: Lu, Binghang, et al.
Publicado: (2026)

Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
por: Xie, Xingyu, et al.
Publicado: (2022)

How Do Diffusion Models Improve Adversarial Robustness?
por: Yuezhang, Liu, et al.
Publicado: (2025)

Scalable and Adaptive Spectral Embedding for Attributed Graph Clustering
por: Liu, Yunhui, et al.
Publicado: (2024)

How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policies
por: Kalra, Akansha, et al.
Publicado: (2025)

Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization
por: Topollai, Kristi, et al.
Publicado: (2025)

Visual Perturbation and Adaptive Hard Negative Contrastive Learning for Compositional Reasoning in Vision-Language Models
por: Huang, Xin, et al.
Publicado: (2025)

TrasMuon: Trust-Region Adaptive Scaling for Orthogonalized Momentum Optimizers
por: Cheng, Peng, et al.
Publicado: (2026)

Revisiting Random Weight Perturbation for Efficiently Improving Generalization
por: Li, Tao, et al.
Publicado: (2024)

Non-native Quantum Generative Optimization with Adversarial Autoencoders
por: Wilson, Blake A., et al.
Publicado: (2024)

HOME-3: High-Order Momentum Estimator with Third-Power Gradient for Convex and Smooth Nonconvex Optimization
por: Zhang, Wei, et al.
Publicado: (2025)

APEX: Probing Neural Networks via Activation Perturbation
por: Ren, Tao, et al.
Publicado: (2026)

TsallisPGD: Adaptive Gradient Weighting for Adversarial Attacks on Semantic Segmentation
por: Matyasko, Alexander, et al.
Publicado: (2026)

Low Rank Adaptation for Adversarial Perturbation
por: Liu, Han, et al.
Publicado: (2026)

Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification
por: Li, Shuai, et al.
Publicado: (2024)

Self-Supervised Learning for Sparse Matrix Reordering
por: Li, Ziwei, et al.
Publicado: (2026)

On the Effects of Adversarial Perturbations on Distribution Robustness
por: Wang, Yipei, et al.
Publicado: (2026)

Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning
por: Wei, Honghao, et al.
Publicado: (2024)