dn 0 the goal is to nd or estimate or learn a

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

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...
View Full Document

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.

Ask a homework question - tutors are online