Difference between revisions of "CATS-Nov-21-2014"

From Theory
(Created page with "== Title == Frequency Moments of Data Streams == Speaker == Brian Brubach == Abstract == Given a massive data set and limited space, what can we learn from a single pass thr...")
 
 
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The topics discussed in this talk are from Chapter 7.1 of the Hopcroft-Kannan book:
 
The topics discussed in this talk are from Chapter 7.1 of the Hopcroft-Kannan book:
https://www.cs.cmu.edu/~venkatg/teaching/CStheory-infoage/hopcroft-kannan-feb2012.pdf
+
http://www.cs.cornell.edu/jeh/book11April2014.pdf

Latest revision as of 21:36, 19 November 2014

Title[edit]

Frequency Moments of Data Streams

Speaker[edit]

Brian Brubach

Abstract[edit]

Given a massive data set and limited space, what can we learn from a single pass through the data? This talk will serve as an introduction to streaming algorithms for frequency moments in big data. I will present algorithms for problems such as counting the number of distinct elements in a data stream and finding high frequency elements.

The topics discussed in this talk are from Chapter 7.1 of the Hopcroft-Kannan book: http://www.cs.cornell.edu/jeh/book11April2014.pdf