Cover Image

Adversarial Machine Learning: Bayesian Perspectives

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Insua, David Rios, Naveiro, Roi, Gallego, Victor, Poulos, Jason
Format:	Preprint
Published:	2020
Subjects:	Artificial Intelligence Machine Learning Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Protecting Classifiers From Attacks
by: Gallego, Victor, et al.
Published: (2020)

Evasion Attacks Against Bayesian Predictive Models
by: Arce, Pablo G., et al.
Published: (2025)

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

Simulation Based Bayesian Optimization
by: Naveiro, Roi, et al.
Published: (2024)

Manipulating hidden-Markov-model inferences by corrupting batch data
by: Caballero, William N., et al.
Published: (2024)

An Adversarial Perspective on Machine Unlearning for AI Safety
by: Łucki, Jakub, et al.
Published: (2024)

Poisoning Bayesian Inference via Data Deletion and Replication
by: Carreau, Matthieu, et al.
Published: (2025)

Personalized Pricing Decisions Through Adversarial Risk Analysis
by: Rasines, Daniel García, et al.
Published: (2024)

LyS at SemEval 2025 Task 8: Zero-Shot Code Generation for Tabular QA
by: Gude, Adrián, et al.
Published: (2025)

Metal-Sci: A Scientific Compute Benchmark for Evolutionary LLM Kernel Search on Apple Silicon
by: Gallego, Víctor
Published: (2026)

Military Applications of Machine Learning: A Bibliometric Perspective
by: Galán, José Javier, et al.
Published: (2024)

Computational adversarial risk analysis for general security games
by: Camacho, Jose Manuel, et al.
Published: (2025)

Navigating Cultural Chasms: Exploring and Unlocking the Cultural POV of Text-To-Image Models
by: Ventura, Mor, et al.
Published: (2023)

Interpretable Machine Learning for TabPFN
by: Rundel, David, et al.
Published: (2024)

Practical Machine Learning for Aphasic Discourse Analysis
by: Pittman, Jason M., et al.
Published: (2025)

Putnam's Critical and Explanatory Tendencies Interpreted from a Machine Learning Perspective
by: Soudin, Sheldon Z.
Published: (2025)

Adversarial Attacks on Machine Learning-Aided Visualizations
by: Fujiwara, Takanori, et al.
Published: (2024)

\mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments
by: Nodehi, Hanzaleh Akbari, et al.
Published: (2026)

Trustworthy Machine Learning under Social and Adversarial Data Sources
by: Shao, Han
Published: (2024)

Evaluating Explanatory Capabilities of Machine Learning Models in Medical Diagnostics: A Human-in-the-Loop Approach
by: Bobes-Bascarán, José, et al.
Published: (2024)

Generative AI Agents in Autonomous Machines: A Safety Perspective
by: Jabbour, Jason, et al.
Published: (2024)

Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning
by: Liu, Qihao, et al.
Published: (2025)

Analyzing the Impact of Adversarial Examples on Explainable Machine Learning
by: Devabhakthini, Prathyusha, et al.
Published: (2023)

Differential Information Distribution: A Bayesian Perspective on Direct Preference Optimization
by: Won, Yunjae, et al.
Published: (2025)

Augmented Probability Simulation Methods for Sequential Games
by: Ekin, Tahir, et al.
Published: (2019)

Bayesian Off-Policy Evaluation and Learning for Large Action Spaces
by: Aouali, Imad, et al.
Published: (2024)

Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
by: Duan, Tianyang, et al.
Published: (2025)

Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective
by: Gallego, Victor
Published: (2023)

Survey of Computerized Adaptive Testing: A Machine Learning Perspective
by: Zhuang, Yan, et al.
Published: (2024)

Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning
by: Rossolini, Giulio, et al.
Published: (2025)

Adversarial Machine Learning Threats to Spacecraft
by: Thummala, Rajiv, et al.
Published: (2024)

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling
by: Aouali, Imad, et al.
Published: (2024)

Predicting Decisions of AI Agents from Limited Interaction through Text-Tabular Modeling
by: Shapira, Eilam, et al.
Published: (2026)

Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
by: Jesson, Andrew, et al.
Published: (2024)

Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective
by: Liu, Yu-An, et al.
Published: (2024)

Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
by: Feng, Yunzhen, et al.
Published: (2024)

A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers
by: Tarasov, Roman, et al.
Published: (2025)

Adversarial Reinforcement Learning for Large Language Model Agent Safety
by: Wang, Zizhao, et al.
Published: (2025)

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
by: Krishna, Satyapriya, et al.
Published: (2022)

RLAC: Reinforcement Learning with Adversarial Critic for Free-Form Generation Tasks
by: Wu, Mian, et al.
Published: (2025)