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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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2 results for “GUHA”
Thompson Sampling Is 2-Competitive for Mistakesstat.ML

Thompson Sampling is at most twice as bad as any other policy in Bayesian bandit models.

problem Optimizing selection of the best arm in Bayesian bandit models with independent latent processes.
method Thompson Sampling approach applied to models with independent latent arm processes.
result Thompson Sampling makes at most twice the expected number of mistakes compared to any other policy.
Thompson SamplingBayesian BanditsMistakesIndependent ProcessesOptimization
2026-07-14abs ↗pdf ↗