Pages that link to "Item:Q1670100"
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The following pages link to Exact worst-case convergence rates of the proximal gradient method for composite convex minimization (Q1670100):
Displaying 27 items.
- Adaptive restart of the optimized gradient method for convex optimization (Q1670019) (← links)
- On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions (Q1679617) (← links)
- Optimizing the efficiency of first-order methods for decreasing the gradient of smooth convex functions (Q2026726) (← links)
- Analysis of optimization algorithms via sum-of-squares (Q2046552) (← links)
- A frequency-domain analysis of inexact gradient methods (Q2149575) (← links)
- Global complexity analysis of inexact successive quadratic approximation methods for regularized optimization under mild assumptions (Q2200083) (← links)
- Efficient first-order methods for convex minimization: a constructive approach (Q2205976) (← links)
- New analysis of linear convergence of gradient-type methods via unifying error bound conditions (Q2297652) (← links)
- A note on the optimal convergence rate of descent methods with fixed step sizes for smooth strongly convex functions (Q2671453) (← links)
- The exact worst-case convergence rate of the gradient method with fixed step lengths for \(L\)-smooth functions (Q2673524) (← links)
- Tight Sublinear Convergence Rate of the Proximal Point Algorithm for Maximal Monotone Inclusion Problems (Q3300773) (← links)
- Convergence Rates of Proximal Gradient Methods via the Convex Conjugate (Q4620416) (← links)
- Analysis of Optimization Algorithms via Integral Quadratic Constraints: Nonstrongly Convex Problems (Q4687235) (← links)
- A splitting method for the locality regularized semi-supervised subspace clustering (Q5110316) (← 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)
- Convergence rate analysis of proximal gradient methods with applications to composite minimization problems (Q5151529) (← links)
- An Unrolled Implicit Regularization Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging with Convergence Guarantee (Q6057272) (← links)
- Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods (Q6120850) (← links)
- An elementary approach to tight worst case complexity analysis of gradient based methods (Q6165581) (← links)
- Principled analyses and design of first-order methods with inexact proximal operators (Q6165584) (← links)
- Polynomial preconditioners for regularized linear inverse problems (Q6541910) (← links)
- Online composite optimization with time-varying regularizers (Q6559338) (← links)
- Forward-backward algorithm for functions with locally Lipschitz gradient: applications to mean field games (Q6564759) (← 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)
- PEPIT: computer-assisted worst-case analyses of first-order optimization methods in python (Q6645946) (← links)
