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Found 3 papers, 1 papers with code
Benefits of Monotonicity in Safe Exploration with Gaussian Processes
We consider the problem of sequentially maximising an unknown function over a set of actions while ensuring that every sampled point has a function value below a given safety threshold.
Stochastic Linear Bandits Robust to Adversarial Attacks
We consider a stochastic linear bandit problem in which the rewards are not only subject to random noise, but also adversarial attacks subject to a suitable budget $C$ (i. e., an upper bound on the sum of corruption magnitudes across the time horizon).
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
Our model has the form of a variational autoencoder, with a Gaussian mixture prior on the latent vector.
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