1.0Microsoft Researchhttps://www.microsoft.com/en-us/researchBrenda Pottshttps://www.microsoft.com/en-us/research/people/v-brpotts/Understanding the Eluder Dimension - Microsoft Researchrich600338<blockquote class="wp-embedded-content" data-secret="KCGml2fC6A"><a href="https://www.microsoft.com/en-us/research/publication/understanding-the-eluder-dimension/">Understanding the Eluder Dimension</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/understanding-the-eluder-dimension/embed/#?secret=KCGml2fC6A" width="600" height="338" title="“Understanding the Eluder Dimension” — Microsoft Research" data-secret="KCGml2fC6A" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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We provide new insights on eluder dimension, a complexity measure that has been extensively used to bound the regret of algorithms for online bandits and reinforcement learning with function approximation. First, we study the relationship between the eluder dimension for a function class and a generalized notion of rank, defined for any monotone “activation” σ:R→R, which […]