Paper amortizes Thompson sampling for simulator-based design
Precomputed approximations enable information-directed sampling and are shown on two synthetic-biology simulators with intractable likelihoods.
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Stories tagged #thompson-sampling
Bayesian Learning to Select Fair Classifiers
Researchers use Thompson Sampling to pick classifiers that balance accuracy and subgroup fairness online.
Expected Sample Complexity in Multi-Armed Bandits
A new expected sample-complexity measure for stochastic bandits separates known and unknown suboptimality and rules out deterministic algorithms.
When May a Bandit Leave Its Anchor? E-Process-Authorized Thompson Sampling under Non-stationarity
Paper proposes e-process-authorized Thompson sampling (e-ATS), using anytime-valid e-processes to decide when bandits may forget history under non-stationary rewards.