1.0Microsoft Researchhttps://www.microsoft.com/en-us/researchalyssahttps://www.microsoft.com/en-us/research/people/alyssa/Spectral Thompson sampling - Microsoft Researchrich600338<blockquote class="wp-embedded-content" data-secret="VkhQbbnMyw"><a href="https://www.microsoft.com/en-us/research/publication/spectral-thompson-sampling-2/">Spectral Thompson sampling</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/spectral-thompson-sampling-2/embed/#?secret=VkhQbbnMyw" width="600" height="338" title="“Spectral Thompson sampling” — Microsoft Research" data-secret="VkhQbbnMyw" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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Thompson Sampling (TS) has attracted a lot of interest due to its good empirical performance, in particular in the computational advertising. Though successful, the tools for its performance analysis appeared only recently. In this paper, we describe and analyze SpectralTS algorithm for a bandit problem, where the payoffs of the choices are smooth given an […]