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Now, assume we have 2 users, 3 movies, and a 2 by 3 matrix Y given by Y = [ 1 8 ? 2 ?
Now, assume we have users, movies, and a by matrix given by
Our goal is to find and such that closely approximates the observed ratings in We want
also to encourage to be 'simple' in the sense that their entries are small; we quantify the strength of this
encouragement by a parameter so that our optimal solution depends on BEGIN SIDENOTE: This
encouragement resolves cases that are strictly ambiguous for example, in
that could be a product of or a product ; we regard the former as more
parsimonious, unless special domain knowledge suggests otherwise Moreover, this encouragement slightly
dampens our and entries toward zero, even in nonambiguous cases. It's like a TA tells you they enjoy the
movie The Shining. If the TA was a true psychological horror fan, that would match the data perfectly. But
maybe the TA just happened to like that movie's particulars. So there are multiple explanations. Seeing data
increases our belief in that data's explanations; but when there are multiple explanations for the data, we
spread out that increase over the multiple explanations. So we don't increase our belief in a particular
explanation as much as we would increase it if other explanations were unavailable. In the case of unknown
and evidence that they approximately multiply to be some known does not mean we should guess
values of that exactly multiply to even if we impose no lowrank constraints. To guess values of
that exactly multiply to is like guessing values for the TA's horrorfilm fanhood that maximally explain the
TA's comment about The Shining : to do so fails to account for inherent plausibility and the presence of
competing explanations. END SIDENOTE
Assume we start by fixing to initial values of Find the optimal vector in this case.
Express your answer in terms of
The first element of is:
The second element of is:
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