Pages that link to "Item:Q2330652"
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The following pages link to Oracle complexity of second-order methods for smooth convex optimization (Q2330652):
Displaying 33 items.
- Complexity bounds for second-order optimality in unconstrained optimization (Q657654) (← links)
- On the oracle complexity of smooth strongly convex minimization (Q2052164) (← links)
- A control-theoretic perspective on optimal high-order optimization (Q2089793) (← links)
- On lower iteration complexity bounds for the convex concave saddle point problems (Q2149573) (← links)
- A simple method for convex optimization in the oracle model (Q2164690) (← links)
- Lower bounds for finding stationary points I (Q2205972) (← links)
- Lower bounds for finding stationary points II: first-order methods (Q2220663) (← links)
- Implementable tensor methods in unconstrained convex optimization (Q2227532) (← links)
- Superfast second-order methods for unconstrained convex optimization (Q2664892) (← links)
- Affine-invariant contracting-point methods for convex optimization (Q2687041) (← links)
- OFFO minimization algorithms for second-order optimality and their complexity (Q2696918) (← links)
- On the oracle complexity of first-order and derivative-free algorithms for smooth nonconvex minimization (Q2902870) (← links)
- (Q4633055) (← links)
- (Q4637040) (← 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)
- Inexact High-Order Proximal-Point Methods with Auxiliary Search Procedure (Q5013580) (← links)
- An Optimal High-Order Tensor Method for Convex Optimization (Q5026443) (← links)
- (Q5053207) (← 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)
- 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)
- An accelerated regularized Chebyshev-Halley method for unconstrained optimization (Q6542872) (← links)
- Inexact tensor methods and their application to stochastic convex optimization (Q6585820) (← links)
- A search-free \(O(1/k^{3/2})\) homotopy inexact proximal-Newton extragradient algorithm for monotone variational inequalities (Q6622750) (← links)
- High-order methods beyond the classical complexity bounds: inexact high-order proximal-point methods (Q6634529) (← links)
- Near-optimal tensor methods for minimizing the gradient norm of convex functions and accelerated primal–dual tensor methods (Q6644994) (← links)
- SketchySGD: reliable stochastic optimization via randomized curvature estimates (Q6664471) (← links)
- Perseus: a simple and optimal high-order method for variational inequalities (Q6665392) (← links)
