Convergence rates of subgradient methods for quasi-convex optimization problems
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Publication:782917
DOI10.1007/s10589-020-00194-yzbMath1447.90039arXiv1910.10879OpenAlexW3025004485MaRDI QIDQ782917
Carisa Kwok Wai Yu, Yao-Hua Hu, Jia-Wen Li
Publication date: 29 July 2020
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1910.10879
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Numerical methods based on nonlinear programming (49M37)
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Cites Work
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- Primal-dual subgradient methods for convex problems
- An inexact proximal method for quasiconvex minimization
- An extension of proximal methods for quasiconvex minimization on the nonnegative orthant
- Handbook of generalized convexity and generalized monotonicity
- Dual subgradient method with averaging for optimal resource allocation
- A scalarization proximal point method for quasiconvex multiobjective minimization
- Projected subgradient methods with non-Euclidean distances for non-differentiable convex minimization and variational inequalities
- Subgradient methods for saddle-point problems
- Finite termination of the proximal point algorithm
- Generalized concavity
- Conditional subgradient optimization -- theory and applications
- New computational guarantees for solving convex optimization problems with first order methods, via a function growth condition measure
- From error bounds to the complexity of first-order descent methods for convex functions
- A unified approach to error bounds for structured convex optimization problems
- \(\ell _p\) regularized low-rank approximation via iterative reweighted singular value minimization
- Linear convergence of epsilon-subgradient descent methods for a class of convex functions
- A generalized subgradient method with relaxation step
- On properties of supporting and quasi-supporting vectors
- Modified inexact Levenberg-Marquardt methods for solving nonlinear least squares problems
- A linear scalarization proximal point method for quasiconvex multiobjective minimization
- Faster subgradient methods for functions with Hölderian growth
- Steepest descent method with a generalized Armijo search for quasiconvex functions on Riemannian manifolds
- Inexact subgradient methods for quasi-convex optimization problems
- Incremental Subgradient Methods for Nondifferentiable Optimization
- On Convergence Rates of Linearized Proximal Algorithms for Convex Composite Optimization with Applications
- Weak Sharp Minima in Mathematical Programming
- Portfolio Optimization with Quasiconvex Risk Measures
- Incremental Subgradients for Constrained Convex Optimization: A Unified Framework and New Methods
- On convergence rates of subgradient optimization methods
- Nonlinear programming methods in the presence of noise
- Surpassing Gradient Descent Provably: A Cyclic Incremental Method with Linear Convergence Rate
- Convergence of Approximate and Incremental Subgradient Methods for Convex Optimization
- On Convergence Properties of a Subgradient Method
- Weak Sharp Minima: Characterizations and Sufficient Conditions
- Abstract convergence theorem for quasi-convex optimization problems with applications
- On the Convergence Rate of Incremental Aggregated Gradient Algorithms
- Linear convergence of CQ algorithms and applications in gene regulatory network inference
- Proximal Point Algorithms on Hadamard Manifolds: Linear Convergence and Finite Termination
- A Unified Augmented Lagrangian Approach to Duality and Exact Penalization
- Normal characterization of the main classes of quasiconvex functions
- Convergence and efficiency of subgradient methods for quasiconvex minimization
