Uzzawa
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@ -121,12 +121,6 @@ central path C converges to anything then $\tau$ approaches zero, therefore
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leading the path to the constrained minimizer while keeping $x$ and $s$
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positive but at the same time minimizing their pairwise products to zero.
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In practice, most central path implementation use Newton steps toward points on
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$\mathcal{C}$ for which $\tau > 0$, rather than pure Newton steps for $F$. This
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is usually possible since those newton steps are biased to stay in the
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hyperspace region where $x > 0$ and $s > 0$ even without enforcing these
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constraints.
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# Exercise 2
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## Exercise 2.1
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@ -213,27 +207,8 @@ constrained minimizer.
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# Exercise 3
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## Exercise 3.1
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<!--
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I consider the given problem, which is exactly the same as one of the problems
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of the previous assignment (Homework 4):
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$$\min_{x} f(x) = 3x^2_1 + 2x_1x_2 + x_1x_3 +
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2.5x^2_2 + 2x_2x_3 + 2x^2_3 - 8x_1 - 3x_2 - 3x_3
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$$$$\text{ subject to } x_1 + x_3 = 3 \;\;\; x_2 + x_3 = 0$$
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defining $x$ as $(x_1,\,x_2,\,x_3)^T$, that can be written in the form of a
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quadratic minimization problem:
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$$\min_{x} f(x) = \dfrac{1}{2} \langle x,\, Gx\rangle + \langle x,\, c\rangle \\
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\text{ subject to } Ax = b$$
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Where $G\in \mathbb{R}^{n\times n}$ is a symmetric positive definite matrix,
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$x$, $c \in \mathbb{R}^n$. The equality constraints are defined in terms of the
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matrix $A\in \mathbb{R}^{m\times n}$, with $m \leq n$ and vector $b \in
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\mathbb{R}^m$. Here, matrix $A$ has full rank.
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-->
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Yes, the problem can be solved with _Uzzawa_'s method since the problem can be
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Yes, the problem can be solved with Uzawa's method since the problem can be
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reformulated as a saddle point system. The KKT conditions of the problem can be
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reformulated as a matrix-vector to vector equality in the following way:
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@ -256,7 +231,7 @@ g\\
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h
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\end{bmatrix}$$
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This is the system the _Uzzawa_ method will solve. Therefore, we need to check
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This is the system the Uzawa method will solve. Therefore, we need to check
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if the matrix:
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$$K = \begin{bmatrix}G & A^T \\ A& 0\end{bmatrix} = \begin{bmatrix}
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@ -279,7 +254,7 @@ $$\begin{bmatrix}
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8.7663\end{bmatrix}$$
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Therefore, the system is indeed a saddle point system and it can be solved with
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_Uzzawa_'s method.
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Uzawa's method.
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## Exercise 3.2
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