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Unformatted text preview: systems the problem arises when we have multiple camera views of a
scene, which give us noisy measurements of a set of features. A feature correspondence algorithm
guesses which features in one view correspond to features in other views. If we make some feature
correspondence errors, we have the present problem.
5.13 Fitting with censored data. In some experiments there are two kinds of measurements or data
available: The usual ones, in which you get a number (say), and censored data, in which you don’t
get the speciﬁc number, but are told something about it, such as a lower bound. A classic example
is a study of lifetimes of a set of subjects (say, laboratory mice). For those who have died by the end
of data collection, we get the lifetime. For those who have not died by the end of data collection,
we do not have the lifetime, but we do have a lower bound, i.e., the length of the study. These are
the censored data values.
We wish to ﬁt a set of data points,
(x(1) , y (1) ), . . . , (x(K ) , y (K ) ),
with x(k) ∈ Rn and y (k) ∈ R, with a linear model of the form y ≈ c...
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This note was uploaded on 09/10/2013 for the course C 231 taught by Professor F.borrelli during the Fall '13 term at University of California, Berkeley.
- Fall '13
- The Aeneid