Prefer a chat interface with context about you and your work?
Hybrid Conditional Gradient-Smoothing Algorithms with Applications to Sparse and Low Rank Regularization
Inspired by such algorithms, in this chapter we study a first-order method for solving certain convex optimization problems. We focus on problems of the formmin {f(x) + g(Ax) + ω(x) : x ∈ H} (3.1) over a real Hilbert spaceH. We assume that f is a convex function with Hölder …