Shranjeno v:
| Main Authors: | Starnes, Andrew, Dereventsov, Anton, Webster, Clayton |
|---|---|
| Format: | Preprint |
| Izdano: |
2023
|
| Teme: | |
| Online dostop: | https://arxiv.org/abs/2311.00521 |
| Oznake: |
Označite
Brez oznak, prvi označite!
|
Podobne knjige/članki
Dimension-free estimators of gradients of functions with(out) non-independent variables
od: Lamboni, Matieyendou
Izdano: (2025)
od: Lamboni, Matieyendou
Izdano: (2025)
Constrained Consensus-Based Optimization and Numerical Heuristics for the Few Particle Regime
od: Beddrich, Jonas, et al.
Izdano: (2024)
od: Beddrich, Jonas, et al.
Izdano: (2024)
A particle consensus approach to solving nonconvex-nonconcave min-max problems
od: Borghi, Giacomo, et al.
Izdano: (2024)
od: Borghi, Giacomo, et al.
Izdano: (2024)
Well-posedness and mean-field limit estimate of a consensus-based algorithm for min-max problems
od: Huang, Hui, et al.
Izdano: (2026)
od: Huang, Hui, et al.
Izdano: (2026)
A New Two-dimensional Model-based Subspace Method for Large-scale Unconstrained Derivative-free Optimization: 2D-MoSub
od: Xie, Pengcheng, et al.
Izdano: (2023)
od: Xie, Pengcheng, et al.
Izdano: (2023)
On the Global Convergence of Particle Swarm Optimization Methods
od: Huang, Hui, et al.
Izdano: (2022)
od: Huang, Hui, et al.
Izdano: (2022)
Consistency of sample-based stationary points for infinite-dimensional stochastic optimization
od: Milz, Johannes
Izdano: (2023)
od: Milz, Johannes
Izdano: (2023)
Linesearch-free adaptive Bregman proximal gradient for convex minimization without relative smoothness
od: Ou, Hongjia, et al.
Izdano: (2025)
od: Ou, Hongjia, et al.
Izdano: (2025)
Spectral conjugate gradient projection methods for large-scale monotone equations without Lipschitz continuity
od: Hamiss, Kabenge, et al.
Izdano: (2026)
od: Hamiss, Kabenge, et al.
Izdano: (2026)
Consensus-Based Optimization Methods Converge Globally
od: Fornasier, Massimo, et al.
Izdano: (2021)
od: Fornasier, Massimo, et al.
Izdano: (2021)
Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law
od: Fornasier, Massimo, et al.
Izdano: (2021)
od: Fornasier, Massimo, et al.
Izdano: (2021)
Penalty decomposition derivative free method for the minimization of partially separable functions over a convex feasible set
od: Cecere, Francesco, et al.
Izdano: (2025)
od: Cecere, Francesco, et al.
Izdano: (2025)
On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms
od: Latafat, Puya, et al.
Izdano: (2023)
od: Latafat, Puya, et al.
Izdano: (2023)
A novel numerical method tailored for unconstrained optimization problems
od: Li, Lin, et al.
Izdano: (2025)
od: Li, Lin, et al.
Izdano: (2025)
Steering exact penalty DCA for nonsmooth DC optimization problems with equality and inequality constraints
od: Dolgopolik, M. V.
Izdano: (2021)
od: Dolgopolik, M. V.
Izdano: (2021)
A Unified Zeroth-Order Proximal Newton-Type Framework for Composite Optimization
od: Liu, Zekun, et al.
Izdano: (2026)
od: Liu, Zekun, et al.
Izdano: (2026)
Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians
od: Zhang, Chenyu, et al.
Izdano: (2023)
od: Zhang, Chenyu, et al.
Izdano: (2023)
PDFO: A Cross-Platform Package for Powell's Derivative-Free Optimization Solvers
od: Ragonneau, Tom M., et al.
Izdano: (2023)
od: Ragonneau, Tom M., et al.
Izdano: (2023)
Projection-based curve pattern search for black-box optimization over smooth convex sets
od: Jia, Xiaoxi, et al.
Izdano: (2025)
od: Jia, Xiaoxi, et al.
Izdano: (2025)
On the convergence of proximal gradient methods for convex simple bilevel optimization
od: Latafat, Puya, et al.
Izdano: (2023)
od: Latafat, Puya, et al.
Izdano: (2023)
Efficient parameter-free restarted accelerated gradient methods for convex and strongly convex optimization
od: Sujanani, Arnesh, et al.
Izdano: (2024)
od: Sujanani, Arnesh, et al.
Izdano: (2024)
Kinetic description and convergence analysis of genetic algorithms for global optimization
od: Borghi, Giacomo, et al.
Izdano: (2023)
od: Borghi, Giacomo, et al.
Izdano: (2023)
An interior point method for nonlinear constrained derivative-free optimization
od: Brilli, Andrea, et al.
Izdano: (2021)
od: Brilli, Andrea, et al.
Izdano: (2021)
BUP-TR: Bayesian Underdetermined Projection Trust-Region Methods for Derivative-Free Optimization
od: Hu, Wei, et al.
Izdano: (2026)
od: Hu, Wei, et al.
Izdano: (2026)
MATRO: Metric-Aware Trust-Region Optimization with Fully Quadratic Models
od: Hu, Wei, et al.
Izdano: (2026)
od: Hu, Wei, et al.
Izdano: (2026)
Nonlinear Derivative-free Constrained Optimization with a Penalty-Interior Point Method and Direct Search
od: Brilli, Andrea, et al.
Izdano: (2024)
od: Brilli, Andrea, et al.
Izdano: (2024)
Uniform-in-time mean-field limit estimate for the Consensus-Based Optimization
od: Huang, Hui, et al.
Izdano: (2024)
od: Huang, Hui, et al.
Izdano: (2024)
Convergence rate of the (1+1)-evolution strategy on locally strongly convex functions with lipschitz continuous gradient
od: Morinaga, Daiki, et al.
Izdano: (2022)
od: Morinaga, Daiki, et al.
Izdano: (2022)
Privacy-Preserving Black-Box Optimization (PBBO): Theory and the Model-Based Algorithm DFOp
od: Xie, Pengcheng
Izdano: (2025)
od: Xie, Pengcheng
Izdano: (2025)
Adaptive proximal gradient methods are universal without approximation
od: Oikonomidis, Konstantinos A., et al.
Izdano: (2024)
od: Oikonomidis, Konstantinos A., et al.
Izdano: (2024)
A derivative-free trust-region approach for Low Order-Value Optimization problems
od: Schwertner, Anderson E., et al.
Izdano: (2025)
od: Schwertner, Anderson E., et al.
Izdano: (2025)
Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient
od: Latafat, Puya, et al.
Izdano: (2023)
od: Latafat, Puya, et al.
Izdano: (2023)
Strong Global Convergence of the Consensus-Based Optimization Algorithm
od: Bonandin, Sabrina, et al.
Izdano: (2025)
od: Bonandin, Sabrina, et al.
Izdano: (2025)
A Structured Proximal Stochastic Variance Reduced Zeroth-order Algorithm
od: Rando, Marco, et al.
Izdano: (2025)
od: Rando, Marco, et al.
Izdano: (2025)
Halpern Acceleration of the Inexact Proximal Point Method of Rockafellar
od: Zhang, Liwei, et al.
Izdano: (2025)
od: Zhang, Liwei, et al.
Izdano: (2025)
Nesterov's accelerated gradient for unbounded convex functions finds the minimum-norm point in the dual space
od: Sakabe, Keiya
Izdano: (2026)
od: Sakabe, Keiya
Izdano: (2026)
Parameter-free accelerated gradient descent for nonconvex minimization
od: Marumo, Naoki, et al.
Izdano: (2022)
od: Marumo, Naoki, et al.
Izdano: (2022)
Optimization of Closed-Loop Shallow Geothermal Systems Using Analytical Models
od: Heinzel, Oliver, et al.
Izdano: (2026)
od: Heinzel, Oliver, et al.
Izdano: (2026)
Surrogate-based categorical neighborhoods for mixed-variable blackbox optimization
od: Audet, Charles, et al.
Izdano: (2026)
od: Audet, Charles, et al.
Izdano: (2026)
CatMADS: Mesh Adaptive Direct Search for constrained blackbox optimization with categorical variables
od: Audet, Charles, et al.
Izdano: (2025)
od: Audet, Charles, et al.
Izdano: (2025)
Podobne knjige/članki
-
Dimension-free estimators of gradients of functions with(out) non-independent variables
od: Lamboni, Matieyendou
Izdano: (2025) -
Constrained Consensus-Based Optimization and Numerical Heuristics for the Few Particle Regime
od: Beddrich, Jonas, et al.
Izdano: (2024) -
A particle consensus approach to solving nonconvex-nonconcave min-max problems
od: Borghi, Giacomo, et al.
Izdano: (2024) -
Well-posedness and mean-field limit estimate of a consensus-based algorithm for min-max problems
od: Huang, Hui, et al.
Izdano: (2026) -
A New Two-dimensional Model-based Subspace Method for Large-scale Unconstrained Derivative-free Optimization: 2D-MoSub
od: Xie, Pengcheng, et al.
Izdano: (2023)