Question

For a given $q \in(0,1]$, recall the set $\mathbb{B}_q\left(R_q\right)$ defined in Equation (11.7) as a model of soft sparsity. (a) A related object is the weak $\ell_q$-ball with parameters $(C, \alpha)$, given by $$ \mathbb{B}_{w(\alpha)}(C):=\left\{\left.\theta \in \mathbb{R}^p| | \theta\right|_{(j)} \leq C j^{-\alpha} \quad \text { for } j=1, \ldots, p\right\} $$ Here $|\theta|_{(j)}$ denote the order statistics of $\theta$ in absolute value, ordered from largest to smallest (so that $|\theta|_{(1)}=\max _{j=1,2, \ldots, p}\left|\theta_j\right|$ and $|\theta|_{(p)}=\min _{j=1,2, \ldots, p}\left|\theta_j\right|$ ) For any $\alpha>1 / q$, show that there is a radius $R_q$ depending on $(C, \alpha)$ such that $\mathbb{B}_{w(\alpha)}(C) \subseteq \mathbb{B}_q\left(R_q\right)$. (b) For a given integer $k \in\{1,2, \ldots, p\}$, the best $k$-term approximation to a vector $\theta^* \in \mathbb{R}^p$ is given by $$ \Pi_k\left(\theta^*\right):=\arg \min _{\|\theta\|_0 \leq k}\left\|\theta-\theta^*\right\|_2^2 $$ Give a closed form expression for $\Pi_k\left(\theta^*\right)$. (c) When $\theta^* \in \mathbb{B}_q\left(R_q\right)$ for some $q \in(0,1]$, show that the best $k$-term approximation satisfies $$ \left\|\Pi_k\left(\theta^*\right)-\theta^*\right\|_2^2 \leq\left(R_q\right)^{2 / q}\left(\frac{1}{k}\right)^{\frac{2}{q}-1} $$

   For a given $q \in(0,1]$, recall the set $\mathbb{B}_q\left(R_q\right)$ defined in Equation (11.7) as a model of soft sparsity.
(a) A related object is the weak $\ell_q$-ball with parameters $(C, \alpha)$, given by

$$
\mathbb{B}_{w(\alpha)}(C):=\left\{\left.\theta \in \mathbb{R}^p| | \theta\right|_{(j)} \leq C j^{-\alpha} \quad \text { for } j=1, \ldots, p\right\}
$$


Here $|\theta|_{(j)}$ denote the order statistics of $\theta$ in absolute value, ordered from largest to smallest (so that $|\theta|_{(1)}=\max _{j=1,2, \ldots, p}\left|\theta_j\right|$ and $|\theta|_{(p)}=\min _{j=1,2, \ldots, p}\left|\theta_j\right|$ ) For any $\alpha>1 / q$, show that there is a radius $R_q$ depending on $(C, \alpha)$ such that $\mathbb{B}_{w(\alpha)}(C) \subseteq \mathbb{B}_q\left(R_q\right)$.
(b) For a given integer $k \in\{1,2, \ldots, p\}$, the best $k$-term approximation to a vector $\theta^* \in \mathbb{R}^p$ is given by

$$
\Pi_k\left(\theta^*\right):=\arg \min _{\|\theta\|_0 \leq k}\left\|\theta-\theta^*\right\|_2^2
$$
Give a closed form expression for $\Pi_k\left(\theta^*\right)$.
(c) When $\theta^* \in \mathbb{B}_q\left(R_q\right)$ for some $q \in(0,1]$, show that the best $k$-term approximation satisfies

$$
\left\|\Pi_k\left(\theta^*\right)-\theta^*\right\|_2^2 \leq\left(R_q\right)^{2 / q}\left(\frac{1}{k}\right)^{\frac{2}{q}-1}
$$


Show more…
Statistical Learning with Sparsity: The Lasso and Generalizations
Statistical Learning with Sparsity: The Lasso and Generalizations
Trevor Hastie,… 1st Edition
Chapter 11, Problem 1 ↓

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7). This is the $\ell_q$-ball with radius $R_q$, defined as: $$\mathbb{B}_q(R_q) = \{\theta \in \mathbb{R}^p : \|\theta\|_q^q = \sum_{j=1}^p |\theta_j|^q \leq R_q^q\}$$ where $q \in (0,1]$.  Show more…

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For a given $q \in(0,1]$, recall the set $\mathbb{B}_q\left(R_q\right)$ defined in Equation (11.7) as a model of soft sparsity. (a) A related object is the weak $\ell_q$-ball with parameters $(C, \alpha)$, given by $$ \mathbb{B}_{w(\alpha)}(C):=\left\{\left.\theta \in \mathbb{R}^p| | \theta\right|_{(j)} \leq C j^{-\alpha} \quad \text { for } j=1, \ldots, p\right\} $$ Here $|\theta|_{(j)}$ denote the order statistics of $\theta$ in absolute value, ordered from largest to smallest (so that $|\theta|_{(1)}=\max _{j=1,2, \ldots, p}\left|\theta_j\right|$ and $|\theta|_{(p)}=\min _{j=1,2, \ldots, p}\left|\theta_j\right|$ ) For any $\alpha>1 / q$, show that there is a radius $R_q$ depending on $(C, \alpha)$ such that $\mathbb{B}_{w(\alpha)}(C) \subseteq \mathbb{B}_q\left(R_q\right)$. (b) For a given integer $k \in\{1,2, \ldots, p\}$, the best $k$-term approximation to a vector $\theta^* \in \mathbb{R}^p$ is given by $$ \Pi_k\left(\theta^*\right):=\arg \min _{\|\theta\|_0 \leq k}\left\|\theta-\theta^*\right\|_2^2 $$ Give a closed form expression for $\Pi_k\left(\theta^*\right)$. (c) When $\theta^* \in \mathbb{B}_q\left(R_q\right)$ for some $q \in(0,1]$, show that the best $k$-term approximation satisfies $$ \left\|\Pi_k\left(\theta^*\right)-\theta^*\right\|_2^2 \leq\left(R_q\right)^{2 / q}\left(\frac{1}{k}\right)^{\frac{2}{q}-1} $$
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