Pages that link to "Item:Q5204822"

The following pages link to Potential-function proofs for gradient methods (Q5204822):

Displaying 9 items.

• A Laplacian approach to \(\ell_1\)-norm minimization (Q2044482) (← links)
• A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives (Q2165600) (← links)
• The rate of convergence of optimization algorithms obtained via discretizations of heavy ball dynamical systems for convex optimization problems (Q5054738) (← links)
• Potential Function-Based Framework for Minimizing Gradients in Convex and Min-Max Optimization (Q5093649) (← links)
• An optimal gradient method for smooth strongly convex minimization (Q6038652) (← links)
• Factor-\(\sqrt{2}\) acceleration of accelerated gradient methods (Q6073850) (← links)
• A Systematic Approach to Lyapunov Analyses of Continuous-Time Models in Convex Optimization (Q6116244) (← links)
• No-regret algorithms in on-line learning, games and convex optimization (Q6120936) (← links)
• The regularized submodular maximization via the Lyapunov method (Q6591625) (← links)