Random Sampling from Data Streams

PhD Qualifying Examination


Title: "Random Sampling from Data Streams"

by

Miss Yu CHEN


Abstract:

Random sampling is the most flexible and fundamental synopsis for large 
datasets. In this survey, we study the problem of how to draw and maintain 
a random sample when the data is given as a stream. We will consider 
different streaming models such as the cash register model, the turnstile 
model, the sliding window model, as well as distributed streams. We will 
also cover different sampling definitions such as l0-sampling and 
lp-sampling. For each problem, we survey existing results and point out 
potential directions for further improvements.


Date:			Monday, 22 June 2015

Time:                  	10:00am - 12:00noon

Venue:                  Room 2129A
                         Lift 19

Committee Members:	Dr. Sunil Arya (Supervisor)
 			Dr. Ke Yi (Supervisor)
 			Prof. Siu-Wing Cheng (Chairperson)
 			Prof. Mordecai Golin


**** ALL are Welcome ****