Prof. Emo Welzl and Prof. Bernd Gärtner
|Mittagsseminar Talk Information|
Date and Time: Tuesday, April 28, 2015, 12:15 pm
Duration: 30 minutes
Location: CAB G51
Speaker: Stephen Chestnut
A data stream can be viewed as a long list of updates to a high dimensional vector. A processor reads the items one-at-a-time, in the order they are given, and is tasked to compute a function of the stream. With applications to distributed computing, databases, and high throughput scientific data, data streaming has emerged as an important model of computation in scenarios where it is impractical or impossible to store the input. This talk first reviews a few of the basic tools used for streaming algorithms and lower bounds. Next, we go on to characterize the space complexity for a large class of functions that generalizes the well-known frequency moments problem and others. This is joint work with Vladimir Braverman and Lin F. Yang at Johns Hopkins University.
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