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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>S&#xE9;bastien Bubeck</author_name><author_url>https://www.microsoft.com/en-us/research/people/sebubeck/</author_url><title>Regret in Online Combinatorial Optimization - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="0wEEUlATpb"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/regret-online-combinatorial-optimization/"&gt;Regret in Online Combinatorial Optimization&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/regret-online-combinatorial-optimization/embed/#?secret=0wEEUlATpb" width="600" height="338" title="&#x201C;Regret in Online Combinatorial Optimization&#x201D; &#x2014; Microsoft Research" data-secret="0wEEUlATpb" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>We address online linear optimization problems when the possible actions of the decision maker are represented by binary vectors. The regret of the decision maker is the difference between her realized loss and the minimal loss she would have achieved by picking, in hindsight, the best possible action. Our goal is to understand the magnitude [&hellip;]</description></oembed>
