:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Benfield, David, Vuong, Phan Tu, Zemkoho, Alain
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2509.22113
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Classification under strategic adversary manipulation using pessimistic bilevel optimisation
por: Benfield, David, et al.
Publicado: (2024)

Adversarial training with restricted data manipulation
por: Benfield, David, et al.
Publicado: (2025)

The Boosted Difference of Convex Functions Algorithm for Value-at-Risk Constrained Portfolio Optimization
por: Thormann, Marah-Lisanne, et al.
Publicado: (2024)

On damage of interpolation to adversarial robustness in regression
por: Peng, Jingfu, et al.
Publicado: (2026)

The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression
por: Hassani, Hamed, et al.
Publicado: (2022)

Primer C-VAE: An interpretable deep learning primer design method to detect emerging virus variants
por: Wang, Hanyu, et al.
Publicado: (2025)

Minimax rates of convergence for nonparametric regression under adversarial attacks
por: Peng, Jingfu, et al.
Publicado: (2024)

Provable tradeoffs in adversarially robust classification
por: Dobriban, Edgar, et al.
Publicado: (2020)

Early stopping and polynomial smoothing in regression with reproducing kernels
por: Averyanov, Yaroslav, et al.
Publicado: (2020)

Minimum discrepancy principle strategy for choosing $k$ in $k$-NN regression
por: Averyanov, Yaroslav, et al.
Publicado: (2020)

Topological safeguard for evasion attack interpreting the neural networks' behavior
por: Echeberria-Barrio, Xabier, et al.
Publicado: (2024)

Task-Driven Discrete Representation Learning
por: Vuong, Tung-Long
Publicado: (2025)

A unifying Bayesian framework for adversarial robustness
por: Arce, Pablo G., et al.
Publicado: (2025)

Countering Overfitting with Counterfactual Examples
por: Giorgi, Flavio, et al.
Publicado: (2025)

Predicting Stock Price Movement with LLM-Enhanced Tweet Emotion Analysis
por: Vuong, An, et al.
Publicado: (2025)

Resurrecting saturated LLM benchmarks with adversarial encoding
por: Ivanov, Igor, et al.
Publicado: (2025)

On adversarial training and the 1 Nearest Neighbor classifier
por: Hagai, Amir, et al.
Publicado: (2024)

Missing value imputation with adversarial random forests -- MissARF
por: Golchian, Pegah, et al.
Publicado: (2025)

Can Go AIs be adversarially robust?
por: Tseng, Tom, et al.
Publicado: (2024)

Lookahead identification in adversarial bandits: accuracy and memory bounds
por: Brukhim, Nataly, et al.
Publicado: (2026)

On robust overfitting: adversarial training induced distribution matters
por: Tian, Runzhi, et al.
Publicado: (2023)

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model
por: Xie, Xinheng, et al.
Publicado: (2024)

Online combinatorial optimization with stochastic decision sets and adversarial losses
por: Neu, Gergely, et al.
Publicado: (2026)

Best of both worlds: Stochastic & adversarial best-arm identification
por: Abbasi-Yadkori, Yasin, et al.
Publicado: (2026)

Resampling strategies for imbalanced regression: a survey and empirical analysis
por: Avelino, Juscimara G., et al.
Publicado: (2025)

Generating artificial digital image correlation data using physics-guided adversarial networks
por: Melching, David, et al.
Publicado: (2023)

Does simple trump complex? Comparing strategies for adversarial robustness in DNNs
por: Brooks, William, et al.
Publicado: (2025)

Masked adversarial neural network for cell type deconvolution in spatial transcriptomics
por: Huang, Lin, et al.
Publicado: (2024)

On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction
por: Wang, Yanwen, et al.
Publicado: (2024)

Generalization ability and Vulnerabilities to adversarial perturbations: Two sides of the same coin
por: Lee, Jung Hoon, et al.
Publicado: (2022)

SHLIME: Foiling adversarial attacks fooling SHAP and LIME
por: Chauhan, Sam, et al.
Publicado: (2025)

Concept activation vectors: a unifying view and adversarial attacks
por: Schnoor, Ekkehard, et al.
Publicado: (2025)

Deep MMD Gradient Flow without adversarial training
por: Galashov, Alexandre, et al.
Publicado: (2024)

Robust estimation with Lasso when outputs are adversarially contaminated
por: Sasai, Takeyuki, et al.
Publicado: (2020)

Rates of convergence for density estimation with generative adversarial networks
por: Puchkin, Nikita, et al.
Publicado: (2021)

Learning to Move Like Professional Counter-Strike Players
por: Durst, David, et al.
Publicado: (2024)

Adaptive and oblivious statistical adversaries are equivalent
por: Blanc, Guy, et al.
Publicado: (2024)

A look at adversarial attacks on radio waveforms from discrete latent space
por: Garuso, Attanasia, et al.
Publicado: (2025)

Evaluating randomized smoothing as a defense against adversarial attacks in trajectory prediction
por: Schumann, Julian F., et al.
Publicado: (2026)

Dual adversarial and contrastive network for single-source domain generalization in fault diagnosis
por: Li, Guangqiang, et al.
Publicado: (2024)