标题
Newton-type methods for non-convex optimization under inexact Hessian information
作者
关键词
-
出版物
MATHEMATICAL PROGRAMMING
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2019-05-23
DOI
10.1007/s10107-019-01405-z
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Sub-sampled Newton methods
- (2018) Farbod Roosta-Khorasani et al. MATHEMATICAL PROGRAMMING
- Complexity and global rates of trust-region methods based on probabilistic models
- (2017) Serge Gratton et al. IMA JOURNAL OF NUMERICAL ANALYSIS
- Global convergence rate analysis of unconstrained optimization methods based on probabilistic models
- (2017) C. Cartis et al. MATHEMATICAL PROGRAMMING
- RandNLA
- (2016) Petros Drineas et al. COMMUNICATIONS OF THE ACM
- Stochastic derivative-free optimization using a trust region framework
- (2016) Jeffrey Larson et al. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
- A trust region algorithm with a worst-case iteration complexity of $$\mathcal{O}(\epsilon ^{-3/2})$$ O ( ϵ - 3 / 2 ) for nonconvex optimization
- (2016) Frank E. Curtis et al. MATHEMATICAL PROGRAMMING
- On the worst-case complexity of nonlinear stepsize control algorithms for convex unconstrained optimization
- (2016) G.N. Grapiglia et al. OPTIMIZATION METHODS & SOFTWARE
- A linear-time algorithm for trust region problems
- (2015) Elad Hazan et al. MATHEMATICAL PROGRAMMING
- Assessing Stochastic Algorithms for Large Scale Nonlinear Least Squares Problems Using Extremal Probabilities of Linear Combinations of Gamma Random Variables
- (2015) Farbod Roosta-Khorasani et al. SIAM-ASA Journal on Uncertainty Quantification
- On the use of iterative methods in cubic regularization for unconstrained optimization
- (2014) Tommaso Bianconcini et al. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
- Convergence of Trust-Region Methods Based on Probabilistic Models
- (2014) A. S. Bandeira et al. SIAM JOURNAL ON OPTIMIZATION
- Stochastic Algorithms for Inverse Problems Involving PDEs and many Measurements
- (2014) Farbod Roosta-Khorasani et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- User-Friendly Tail Bounds for Sums of Random Matrices
- (2011) Joel A. Tropp FOUNDATIONS OF COMPUTATIONAL MATHEMATICS
- Complexity bounds for second-order optimality in unconstrained optimization
- (2011) C. Cartis et al. JOURNAL OF COMPLEXITY
- Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization
- (2011) Coralia Cartis et al. OPTIMIZATION METHODS & SOFTWARE
- Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity
- (2010) Coralia Cartis et al. MATHEMATICAL PROGRAMMING
- On the Complexity of Steepest Descent, Newton's and Regularized Newton's Methods for Nonconvex Unconstrained Optimization Problems
- (2010) C. Cartis et al. SIAM JOURNAL ON OPTIMIZATION
- Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results
- (2009) Coralia Cartis et al. MATHEMATICAL PROGRAMMING
- Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points
- (2009) Andrew R. Conn et al. SIAM JOURNAL ON OPTIMIZATION
- Iterative Methods for Finding a Trust-region Step
- (2009) Jennifer B. Erway et al. SIAM JOURNAL ON OPTIMIZATION
- A recursive Formula-trust-region method for bound-constrained nonlinear optimization
- (2008) S. Gratton et al. IMA JOURNAL OF NUMERICAL ANALYSIS
- Recursive Trust-Region Methods for Multiscale Nonlinear Optimization
- (2008) Serge Gratton et al. SIAM JOURNAL ON OPTIMIZATION
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