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change "frac" to "tfrac"
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docs/src/examples/ls.md

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In this tutorial, we will show how to model and solve the nonconvex nonsmooth least-square problem
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```math
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\min_{x \in \mathbb{R}^n} \frac{1}{2} \|Ax - b\|_2^2 + \lambda \|x\|_0.
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\min_{x \in \mathbb{R}^n} \tfrac{1}{2} \|Ax - b\|_2^2 + \lambda \|x\|_0.
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```
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## Modelling the problem
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We first formulate the objective function as the sum of a smooth function $f$ and a nonsmooth regularizer $h$:
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```math
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\frac{1}{2} \|Ax - b\|_2^2 + \lambda \|x\|_0 = f(x) + h(x),
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\tfrac{1}{2} \|Ax - b\|_2^2 + \lambda \|x\|_0 = f(x) + h(x),
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```
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where
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```math
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\begin{align*}
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f(x) &:= \frac{1}{2} \|Ax - b\|_2^2,\\
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f(x) &:= \tfrac{1}{2} \|Ax - b\|_2^2,\\
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h(x) &:= \lambda\|x\|_0.
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\end{align*}
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```

docs/src/regularizers.md

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The proximal mapping is defined as
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```math
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\text{prox}(\psi, q, \sigma) := \argmin_y \ \psi(y) + \frac{\sigma}{2} \|y - q\|_2^2.
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\text{prox}(\psi, q, \sigma) := \argmin_y \ \psi(y) + \tfrac{\sigma}{2} \|y - q\|_2^2.
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```
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!!! note

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