Tag: ts
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Thompson Sampling-like Algorithms for Stochastic Rising Bandits
Thompson Sampling-like Algorithms for Stochastic Rising Bandits arXiv:2505.12092v1 Announce Type: new Abstract: Stochastic rising rested bandit (SRRB) is a setting where the arms’ expected rewards increase as they are pulled. It models scenarios in which the performances of the different options grow as an effect of an underlying learning process (e.g., online model selection). Even…
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Fast, Precise Thompson Sampling for Bayesian Optimization
Fast, Precise Thompson Sampling for Bayesian Optimization arXiv:2411.17071v1 Announce Type: new Abstract: Thompson sampling (TS) has optimal regret and excellent empirical performance in multi-armed bandit problems. Yet, in Bayesian optimization, TS underperforms popular acquisition functions (e.g., EI, UCB). TS samples arms according to the probability that they are optimal. A recent algorithm, P-Star Sampler (PSS),…