AI RESEARCH
Stable Thompson Sampling: Valid Inference via Variance Inflation
arXiv CS.LG
•
ArXi:2505.23260v2 Announce Type: replace-cross We consider the problem of statistical inference when the data is collected via a Thompson Sampling-type algorithm. While Thompson Sampling (TS) is known to be both asymptotically optimal and empirically effective, its adaptive sampling scheme poses challenges for constructing confidence intervals for model parameters. We propose and analyze a variant of TS, called Stable Thompson Sampling, in which the posterior variance is inflated by a logarithmic factor.