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Found 4 papers, 2 papers with code
Weighted Gaussian Process Bandits for Non-stationary Environments
To this end, we develop WGP-UCB, a novel UCB-type algorithm based on weighted Gaussian process regression.
On the Equivalence between Online and Private Learnability beyond Binary Classification
First, we show that private learnability implies online learnability in both settings.
Randomized Exploration for Non-Stationary Stochastic Linear Bandits
We investigate two perturbation approaches to overcome conservatism that optimism based algorithms chronically suffer from in practice.
On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems
We investigate the optimality of perturbation based algorithms in the stochastic and adversarial multi-armed bandit problems.
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