38 citations · 112 across the 12 of their papers we have counts for
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stat.ML2026
Adversarial observations in probabilistic State-Space Models for robust Reinforcement Learning
M. Santos-Pascual, D. Ríos Insua
Decision-making under partial or adversarial observability requires accurate inference of the environment's latent state and its associated uncertainty. This work analyses adversar…
stat.ML2018★ 24 cited
Stochastic Gradient MCMC with Repulsive Forces
Victor Gallego, David Rios Insua
We propose a unifying view of two different Bayesian inference algorithms, Stochastic Gradient Markov Chain Monte Carlo (SG-MCMC) and Stein Variational Gradient Descent (SVGD), lea…
stat.ML2018★ 38 cited
Adversarial classification: An adversarial risk analysis approach
Roi Naveiro, Alberto Redondo, David Ríos Insua +1
Classification problems in security settings are usually contemplated as confrontations in which one or more adversaries try to fool a classifier to obtain a benefit. Most approach…