Wednesday Apr 18th, 2007
CSE Room 305
12:00 - 1:00 PM
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Statistical Change Detection for Multi-dimensional Data
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Xiuyao Song |
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This talk deals with detecting change of distribution in multi-dimensional
data sets. For a given baseline data set and a set of newly observed data
points, we define a statistical hypothesis test called the density test
for deciding if the observed data points are sampled from the underlying
distribution that produced the baseline data set. We define a test
statistic that is strictly distribution-free under the null hypothesis.
Our experimental results show that the density test has substantially more
power than the two existing methods for multi-dimensional change
detection.
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For
upcoming talks, visit http://www.cise.ufl.edu/dbcenter/seminar.shtml