Pages that link to "Item:Q312663"
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The following pages link to Optimized first-order methods for smooth convex minimization (Q312663):
Displaying 29 items.
- From the Ravine Method to the Nesterov Method and Vice Versa: A Dynamical System Perspective (Q5097023) (← links)
- Rate of convergence of the Nesterov accelerated gradient method in the subcritical case <i>α</i> ≤ 3 (Q5107904) (← links)
- Convergence rate of a relaxed inertial proximal algorithm for convex minimization (Q5110325) (← links)
- First-Order Methods for Nonconvex Quadratic Minimization (Q5113167) (← links)
- Worst-Case Convergence Analysis of Inexact Gradient and Newton Methods Through Semidefinite Programming Performance Estimation (Q5116548) (← links)
- Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection (Q5123997) (← links)
- Fast First-Order Methods for Minimizing Convex Composite Functions (Q5127658) (← links)
- Data-Driven Nonsmooth Optimization (Q5210515) (← links)
- Solving inverse problems using data-driven models (Q5230520) (← links)
- Exact Worst-Case Performance of First-Order Methods for Composite Convex Optimization (Q5275297) (← links)
- Optimal Affine-Invariant Smooth Minimization Algorithms (Q5376450) (← links)
- An acceleration procedure for optimal first-order methods (Q5746718) (← links)
- Robust inference for skewed data in health sciences (Q5865434) (← links)
- An optimal gradient method for smooth strongly convex minimization (Q6038652) (← links)
- Convergence of iterates for first-order optimization algorithms with inertia and Hessian driven damping (Q6042225) (← links)
- Factor-\(\sqrt{2}\) acceleration of accelerated gradient methods (Q6073850) (← links)
- Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods (Q6120850) (← links)
- Principled analyses and design of first-order methods with inexact proximal operators (Q6165584) (← links)
- First-order methods for convex optimization (Q6169988) (← links)
- Conic linear optimization for computer-assisted proofs. Abstracts from the workshop held April 10--16, 2022 (Q6170529) (← links)
- From Halpern's fixed-point iterations to Nesterov's accelerated interpretations for root-finding problems (Q6179877) (← links)
- Provably faster gradient descent via long steps (Q6579999) (← links)
- Tight ergodic sublinear convergence rate of the relaxed proximal point algorithm for monotone variational inequalities (Q6596341) (← links)
- Interpolation conditions for linear operators and applications to performance estimation problems (Q6601207) (← links)
- The exact worst-case convergence rate of the alternating direction method of multipliers (Q6634526) (← links)
- PEPIT: computer-assisted worst-case analyses of first-order optimization methods in python (Q6645946) (← links)
- A distributed accelerated algorithm based on a unified momentum method (Q6655815) (← links)
- Accelerated minimax algorithms flock together (Q6663115) (← links)
- Several kinds of acceleration techniques for unconstrained optimization first-order algorithms (Q6665360) (← links)
