Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency | Paper Citation Record

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This paper cites Eigenvalue-based algorithm and analysis for nonconvex QCQP with one constraint.Mathematical Programming, 173(1-2):79–116, 2019.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Eigenvalue-based algorithm and analysis for nonconvex QCQP with one constraint.Mathematical Programming, 173(1-2):79–116, 2019

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This paper cites Solving the trust- region subproblem by a generalized eigenvalue problem.SIAM Journal on Optimiza- tion, 27(1):269–291, January 2017.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Solving the trust- region subproblem by a generalized eigenvalue problem.SIAM Journal on Optimiza- tion, 27(1):269–291, January 2017

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Inexact tensor methods and their application to stochastic convex opti- mization.Optimization Methods and Software, pages 1–42, 2023

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Advancing the lower bounds: an ac- celerated, stochastic, second-order method with optimal adaptation to inexactness

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Estimate sequence methods: extensions and approximations.Institute for Operations Research, ETH, Z¨ urich, Switzerland, 2(1), 2009

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Knitro: An integrated package for nonlinear optimization.Large-scale nonlinear optimization, pages 35–59, 2006

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This paper cites Op- timal and adaptive monteiro-svaiter acceleration.Advances in Neural Information Pro- cessing Systems, 35:20338–20350, 2022.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Op- timal and adaptive monteiro-svaiter acceleration.Advances in Neural Information Pro- cessing Systems, 35:20338–20350, 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Unresolved cited work

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Adaptive cubic regularisation methods for unconstrained optimization

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This paper cites SIAM, 2022.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency SIAM, 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Accelerating adaptive cubic regularization of newton’s method via random sampling.The Journal of Machine Learning Research, 23(1):3904–3941, 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency SIAM, 2000

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This paper cites A trust region algo- rithm with a worst-case iteration complexity ofO(ϵ −3/2) for nonconvex optimization.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A trust region algo- rithm with a worst-case iteration complexity ofO(ϵ −3/2) for nonconvex optimization

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This paper cites Concise complexity analyses for trust region methods.Optimization Letters, 12:1713–1724, 2018.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Concise complexity analyses for trust region methods.Optimization Letters, 12:1713–1724, 2018

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Trust- region newton-cg with strong second-order complexity guarantees for nonconvex opti- mization.SIAM Journal on Optimization, 31(1):518–544, 2021

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency SIAM, 1996

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Contracting proximal methods for smooth convex optimization.SIAM Journal on Optimization, 30(4):3146–3169, 2020

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Cardinal Optimizer (COPT) User Guide, October 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Accelerated gradient methods for nonconvex non- linear and stochastic programming.Mathematical Programming, 156(1):59–99, 2016

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency On the convergence and worst-case complexity of trust-region and regularization methods for unconstrained optimization.Mathematical Programming, 152(1):491–520, 2015

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A consistently adaptive trust-region method.Advances in Neural Information Processing Systems, 35:6640–6653, 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A simple and practical adaptive trust-region method

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Ho- mogeneous second-order descent framework: a fast alternative to Newton-type meth- ods.Mathematical Programming, May 2025

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A second-order cone based approach for solving the trust-region subproblem and its variants.SIAM Journal on Optimization, 27(3):1485–1512, 2017

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency An approximation-based regularized extra-gradient method for monotone variational inequalities.SIAM Journal on Optimization, 35(3): 1469–1497, 2025

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Inexact and Implementable Accelerated Newton Proximal Extragradient Method for Convex Optimization

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A unified adaptive tensor approximation scheme to accelerate composite convex optimization.SIAM Journal on Optimization, 30(4):2897–2926, 2020

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency An optimal high-order tensor method for convex optimization.Mathematics of Operations Research, 46(4):1390–1412, 2021

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Generalized Optimistic Methods for Convex-Concave Saddle Point Problems

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Accelerated quasi-newton proximal extragradient: Faster rate for smooth convex optimization.Advances in Neural Information Processing Systems, 36, 2024

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency H¨ olderian Error Bounds and Kurdyka- Lojasiewicz In- equality for the Trust Region Subproblem.Mathematics of Operations Research, 47(4): 3025–3050, November 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Be- yond nonconvexity: A universal trust-region method with new analyses.arXiv preprint arXiv:2311.11489, 2024

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency The first optimal acceleration of high-order methods in smooth convex optimization.Advances in Neural Information Processing Systems, 35:35339–35351, 2022

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Explicit Second-Order Min-Max Optimization: Practical Algorithms and Complexity Analysis

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency An accelerated hybrid proximal extra- gradient method for convex optimization and its implications to second-order methods

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Newton’s method

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Accelerating the cubic regularization of newton’s method on convex problems.Mathematical Programming, 112(1):159–181, 2008

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A method for solving the convex programming problem with conver- gence rateO(1/k 2)

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Springer, 2018

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Implementable tensor methods in unconstrained convex optimization

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Springer, 1999

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Tensor methods for strongly convex strongly concave saddle point problems and strongly monotone variational inequalities

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Newton’s method and its use in optimization.European Journal of Operational Research, 181(3):1086–1096, 2007

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency PDFO: a cross-platform package for powell’s derivative-free optimization solvers.Mathematical Programming Computation, pages 1–25, 2024

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Santos, and Danny C

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Trust region policy optimization

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Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Unified acceleration of high-order algorithms under general H¨ older continuity.SIAM Journal on Optimization, 31(3):1797–1826, January 2021

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Resolution: unresolved; no resolver link, observed 2026-08-04T00:40:46.483213Z

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Observation 908eb1da-d5f3-4ecf-a4ac-2af2069ae2e7 · outbound

This paper cites Vavasis and Richard Zippel.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Vavasis and Richard Zippel

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Resolution: unresolved; no resolver link, observed 2026-08-04T00:40:46.485918Z

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Observation 26d9982c-4928-4be6-b955-ecfcbc456993 · outbound

This paper cites The generalized trust region subproblem: solution complexity and convex hull results.Mathematical Programming, 191(2):445– 486, 2022.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency The generalized trust region subproblem: solution complexity and convex hull results.Mathematical Programming, 191(2):445– 486, 2022

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Observation 74ec9abe-a1cb-4d66-8cc2-57fda3a71bec · outbound

This paper cites Accelerated first-order primal-dual proximal methods for linearly con- strained composite convex programming.SIAM Journal on Optimization, 27(3):1459– 1484, 2017.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Accelerated first-order primal-dual proximal methods for linearly con- strained composite convex programming.SIAM Journal on Optimization, 27(3):1459– 1484, 2017

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Resolution: unresolved; no resolver link, observed 2026-08-04T00:40:46.492882Z

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Observation 7bf0c977-1f64-4a0d-8ce8-5a2dca3200df · outbound

This paper cites Accelerated primal–dual proximal block coordinate updating methods for constrained convex optimization.Computational Optimization and Applications, 70(1):91–128, 2018.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Accelerated primal–dual proximal block coordinate updating methods for constrained convex optimization.Computational Optimization and Applications, 70(1):91–128, 2018

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Observation da841b8c-ca8e-4b5e-ae00-b74d24b7b246 · outbound

This paper cites Trust region based adversarial attack on neural networks.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Trust region based adversarial attack on neural networks

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Observation 39eb7744-cc46-40ea-ab6b-379926c552c2 · outbound

This paper cites A New Complexity Result on Minimization of a Quadratic Function with a Sphere Constraint.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A New Complexity Result on Minimization of a Quadratic Function with a Sphere Constraint

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Observation 322b87d6-7178-4ebf-9916-1d788d990916 · outbound

This paper cites Second Order Optimization Algorithms I, 2005.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Second Order Optimization Algorithms I, 2005

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Observation a8a95f65-be5f-4515-9525-7b251c81a1f3 · outbound

This paper cites A review of trust region algorithms for optimization.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency A review of trust region algorithms for optimization

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Observation 6045808d-5c87-4ab2-ad03-9d6047debae6 · outbound

This paper cites Recent advances in trust region algorithms.Mathematical Program- ming, 151:249–281, 2015.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency Recent advances in trust region algorithms.Mathematical Program- ming, 151:249–281, 2015

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Observation cd72cc7f-a0d3-48ac-b911-59dc47cf956f · outbound

This paper cites 1 σ+ ∥y(σ−)−y(σ +)∥+ M σ2 + ∥y(σ−)−y(σ +)∥2 + 2M σ+ ∥y(σ−)−y(σ +)∥ ·ψ+ # +.

Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency 1 σ+ ∥y(σ−)−y(σ +)∥+ M σ2 + ∥y(σ−)−y(σ +)∥2 + 2M σ+ ∥y(σ−)−y(σ +)∥ ·ψ+ # +

Reference 63

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