Pages that link to "Item:Q2227532"
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The following pages link to Implementable tensor methods in unconstrained convex optimization (Q2227532):
Displaying 49 items.
- Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems (Q2042418) (← links)
- Accelerated Bregman proximal gradient methods for relatively smooth convex optimization (Q2044481) (← links)
- An adaptive high order method for finding third-order critical points of nonconvex optimization (Q2079692) (← links)
- A control-theoretic perspective on optimal high-order optimization (Q2089793) (← links)
- Local convergence of tensor methods (Q2133417) (← links)
- Optimal complexity and certification of Bregman first-order methods (Q2149545) (← links)
- Generalized mirror prox algorithm for monotone variational inequalities: Universality and inexact oracle (Q2159456) (← links)
- Smoothness parameter of power of Euclidean norm (Q2178876) (← links)
- Accelerated meta-algorithm for convex optimization problems (Q2656390) (← links)
- Superfast second-order methods for unconstrained convex optimization (Q2664892) (← links)
- Cubic regularization methods with second-order complexity guarantee based on a new subproblem reformulation (Q2676160) (← links)
- Affine-invariant contracting-point methods for convex optimization (Q2687041) (← links)
- Inexact accelerated high-order proximal-point methods (Q2689812) (← links)
- Zeroth-order nonconvex stochastic optimization: handling constraints, high dimensionality, and saddle points (Q2696568) (← links)
- On local convergence of alternating schemes for optimization of convex problems in the tensor train format (Q2840392) (← links)
- Introduction to high-order optimization methods (Q3307337) (← links)
- (Q3675433) (← links)
- Tensor Methods for Unconstrained Optimization Using Second Derivatives (Q4012411) (← links)
- Tensor Methods for Large, Sparse Unconstrained Optimization (Q4377571) (← links)
- Tensor Methods for Minimizing Convex Functions with Hölder Continuous Higher-Order Derivatives (Q4971023) (← links)
- Unified Acceleration of High-Order Algorithms under General Hölder Continuity (Q5003214) (← links)
- Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses (Q5004367) (← links)
- Inexact High-Order Proximal-Point Methods with Auxiliary Search Procedure (Q5013580) (← links)
- An Optimal High-Order Tensor Method for Convex Optimization (Q5026443) (← links)
- Tensor methods for finding approximate stationary points of convex functions (Q5038435) (← links)
- Inexact basic tensor methods for some classes of convex optimization problems (Q5043845) (← links)
- Variants of the A-HPE and large-step A-HPE algorithms for strongly convex problems with applications to accelerated high-order tensor methods (Q5058404) (← links)
- A Unified Adaptive Tensor Approximation Scheme to Accelerate Composite Convex Optimization (Q5131958) (← links)
- Contracting Proximal Methods for Smooth Convex Optimization (Q5139832) (← links)
- A Bregman Forward-Backward Linesearch Algorithm for Nonconvex Composite Optimization: Superlinear Convergence to Nonisolated Local Minima (Q5853567) (← links)
- Dual Space Preconditioning for Gradient Descent (Q5857297) (← links)
- On inexact solution of auxiliary problems in tensor methods for convex optimization (Q5859013) (← links)
- Inexact model: a framework for optimization and variational inequalities (Q5865338) (← links)
- Higher-Order Methods for Convex-Concave Min-Max Optimization and Monotone Variational Inequalities (Q5869812) (← links)
- High-Order Optimization Methods for Fully Composite Problems (Q5869820) (← links)
- Regularized Newton Method with Global \({\boldsymbol{\mathcal{O}(1/{k}^2)}}\) Convergence (Q6116237) (← links)
- Super-Universal Regularized Newton Method (Q6136654) (← links)
- Efficiency of higher-order algorithms for minimizing composite functions (Q6155068) (← links)
- Smooth monotone stochastic variational inequalities and saddle point problems: a survey (Q6160072) (← links)
- First-order methods for convex optimization (Q6169988) (← links)
- Adaptive Third-Order Methods for Composite Convex Optimization (Q6171322) (← links)
- An accelerated regularized Chebyshev-Halley method for unconstrained optimization (Q6542872) (← links)
- Inexact tensor methods and their application to stochastic convex optimization (Q6585820) (← links)
- Convergence analysis of stochastic higher-order majorization–minimization algorithms (Q6586916) (← links)
- Higher-order Newton methods with polynomial work per iteration (Q6608710) (← links)
- A search-free \(O(1/k^{3/2})\) homotopy inexact proximal-Newton extragradient algorithm for monotone variational inequalities (Q6622750) (← links)
- A mirror inertial forward-reflected-backward splitting: convergence analysis beyond convexity and Lipschitz smoothness (Q6644234) (← links)
- Near-optimal tensor methods for minimizing the gradient norm of convex functions and accelerated primal–dual tensor methods (Q6644994) (← links)
- Perseus: a simple and optimal high-order method for variational inequalities (Q6665392) (← links)
