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Theory Lunch Seminar

Wednesday, May 5, 2021 – 12:00pm to 1:00pm

Location:

Virtual Presentation – ET Remote Access – Zoom

Speaker:

SAMSON ZHOU, Postdoctoral Researcher https://samsonzhou.github.io/

Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators

We introduce difference estimators for data stream computation, which provide approximations to F(v)-F(u) for frequency vectors v,u and a given function F. We show how to use such estimators to carefully trade error for memory in an iterative manner. We give the first difference estimators for the frequency moments F_p for p between 0 and 2, as well as for integers p>2. Using these, we resolve a number of central open questions in adversarial robust streaming and sliding window models.

For both models, we obtain algorithms for norm estimation whose dependence on ε is 1/ε2, which shows, up to logarithmic factors, that there is no overhead over the standard insertion-only data stream model for these problems.

Zoom Participation. See announcement.

CMU Theory Youtube channel

Event Website:

http://www.cs.cmu.edu/~theorylunch/abstractsHTML/20210505.html

For More Information, Contact:

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