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Statistical Learning with Sparsity
book

Statistical Learning with Sparsity

by Trevor Hastie, Robert Tibshirani, Martin Wainwright
May 2015
Intermediate to advanced
367 pages
12h 7m
English
Chapman and Hall/CRC
Content preview from Statistical Learning with Sparsity
266 GRAPHS AND MODEL SELECTION
(b) Show how to use the solution θ
12
to update the current version of W and
b
Θ in O(p
2
) operations.
(c) Likewise, show how to move to a new block of equations in O(p
2
) opera-
tions.
(d) You have derived a primal graphical lasso algorithm. Write it down in
algorithmic form, as in Algorithm 9.1
(Mazumder and Hastie 2012)
Ex. 9.8 Derive the conditional distributions (9.29) and (9.30) for the mixed
graphical model.
Ex. 9.9 Close inspection of the pairwise Markov random field model (9.28)
will show that it is overparametrized with respect to the discrete potentials
ρ
sj
and ψ
jr
. This exercise shows that this aliasing is resolved by ...
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Publisher Resources

ISBN: 9781498712163