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  <title><![CDATA[ARC Talk: David Woodruff - IBM]]></title>
  <body><![CDATA[<p align="center"><strong>Algorithms &amp; Randomness Center (ARC)</strong>&nbsp;</p><p align="center"><strong>David Woodruff - IBM<br /></strong><strong>Tuesday, June 7, 2016<br /></strong><strong>Klaus Conference Room 2100 - 2:00 pm</strong>&nbsp;</p><p><strong>Title:<br /></strong>An Optimal Algorithm for Finding L2 Heavy Hitters<br /><br /><strong>Abstract:<br /></strong>We consider the problem of finding the most frequent items in a stream of items from a universe of size n. Namely, we consider returning all l_2-heavy hitters, i.e., those items j for which f_j &gt;= eps sqrt{F_2}, where f_j is the number of occurrences of item j, and F_2 = sum_i f_i^2 is the second moment of the stream. In 2002, Charikar, Chen, and Farach-Colton suggested the CountSketch data structure, which solves this using log^2 n bits of space (for constant eps). The only known lower bound is log n bits. Using Gaussian processes, we show it is possible to achieve an optimal log n bits of space. Our technique resolves a number of other questions in data streams.</p><p>Based on work with Vladimir Braverman, Stephen Chestnut, and Nikita Ivkin (STOC '16) and work with Vladimir Braverman, Stephen Chestnut, Nikita Ivkin, Jelani Nelson, and Zhengyu Wang.<br /><br />Host: Santosh Vempala</p>]]></body>
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      <value><![CDATA[2016-06-07T15:00:00-04:00]]></value>
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      <value><![CDATA[<p>denton at cc dot gatech dot edu</p>]]></value>
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