Exercise · ZW-PROXIMAL-GRADIENT-METHOD-010 · ★★★ Advanced
Minimize \( \tfrac12(x-6)^2+|x| \) over \( \mathbb{R} \) with one proximal gradient step using \( t=1 \) from \( x_0=0 \). What is \( x_1 \)?
Choose one option.
Show answer
- B. \( 5 \)
Exercise · ZW-PROXIMAL-GRADIENT-METHOD-010 · ★★★ Advanced
Choose one option.
The gradient at \( 0 \) is \( -6 \), so \( z=6 \). Applying soft thresholding with \( t\lambda=1 \) gives \( 5 \). Not applying the threshold gives \( 6 \).
Proximal gradient minimizes \( f(x)+g(x) \), with \( f \) convex and smooth and \( g \) convex but possibly nondifferentiable, alternating a gradient step on \( f \) and a proximal step on \( g \).