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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>Yuri Gurevich</author_name><author_url>https://www.microsoft.com/en-us/research/people/gurevich/</author_url><title>Nearly Linear Time - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="3xUQDctJXh"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/nearly-linear-time/"&gt;Nearly Linear Time&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/nearly-linear-time/embed/#?secret=3xUQDctJXh" width="600" height="338" title="&#x201C;Nearly Linear Time&#x201D; &#x2014; Microsoft Research" data-secret="3xUQDctJXh" 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>The notion of linear time is very sensitive to machine model. In this connection we introduce and study class NLT of functions computable in nearly linear time n(log n)O(1) on random access computers or any other &#x201C;reasonable&#x201D; machine model (with the standard multitape Turing machine model being &#x201C;unreasonable&#x201D; for that low complexity class). This gives [&hellip;]</description></oembed>
