Copertina

A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Shuyao, Wright, Stephen J.
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Optimization and Control Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The inexact power augmented Lagrangian method for constrained nonconvex optimization
di: Bodard, Alexander, et al.
Pubblicazione: (2024)

Block majorization-minimization with diminishing radius for constrained nonsmooth nonconvex optimization
di: Lyu, Hanbaek, et al.
Pubblicazione: (2020)

Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes
di: Lan, Guanghui, et al.
Pubblicazione: (2024)

High-probability complexity guarantees for nonconvex minimax problems
di: Laguel, Yassine, et al.
Pubblicazione: (2024)

Learning to optimize with guarantees: a complete characterization of linearly convergent algorithms
di: Martin, Andrea, et al.
Pubblicazione: (2025)

An accelerated first-order regularized momentum descent ascent algorithm for stochastic nonconvex-concave minimax problems
di: Zhang, Huiling, et al.
Pubblicazione: (2023)

General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization
di: Ahn, Kwangjun, et al.
Pubblicazione: (2024)

An adaptively inexact first-order method for bilevel optimization with application to hyperparameter learning
di: Salehi, Mohammad Sadegh, et al.
Pubblicazione: (2023)

An inexact Bregman proximal point method and its acceleration version for unbalanced optimal transport
di: Chen, Xiang, et al.
Pubblicazione: (2024)

An inexact LPA for DC composite optimization and application to matrix completions with outliers
di: Tao, Ting, et al.
Pubblicazione: (2023)

Avoiding strict saddle points of nonconvex regularized problems
di: Bai, Luwei, et al.
Pubblicazione: (2024)

Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization
di: Li, Yuchen, et al.
Pubblicazione: (2023)

Adam with model exponential moving average is effective for nonconvex optimization
di: Ahn, Kwangjun, et al.
Pubblicazione: (2024)

Convergence of SGD with momentum in the nonconvex case: A time window-based analysis
di: Qiu, Junwen, et al.
Pubblicazione: (2024)

Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian
di: He, Chuan, et al.
Pubblicazione: (2023)

On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem
di: Ding, Kuangyu, et al.
Pubblicazione: (2025)

Proximal basin hopping: global optimization with guarantees
di: Lauga, Guillaume, et al.
Pubblicazione: (2026)

Accelerating optimization over the space of probability measures
di: Chen, Shi, et al.
Pubblicazione: (2023)

An inexact $q$-order regularized proximal Newton method for nonconvex composite optimization
di: Liu, Ruyu, et al.
Pubblicazione: (2023)

Towards Weaker Variance Assumptions for Stochastic Optimization
di: Alacaoglu, Ahmet, et al.
Pubblicazione: (2025)

Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
di: Alacaoglu, Ahmet, et al.
Pubblicazione: (2024)

Universal generalization guarantees for Wasserstein distributionally robust models
di: Le, Tam, et al.
Pubblicazione: (2024)

Automatic nonlinear MPC approximation with closed-loop guarantees
di: Tokmak, Abdullah, et al.
Pubblicazione: (2023)

Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
di: Li, Shuyao, et al.
Pubblicazione: (2024)

Convergence rates for an inexact linearized ADMM for nonsmooth nonconvex optimization with nonlinear equality constraints
di: Bourkhissi, Lahcen El, et al.
Pubblicazione: (2025)

A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization
di: Liu, Wei, et al.
Pubblicazione: (2025)

Statistical guarantees for continuous-time policy evaluation: blessing of ellipticity and new tradeoffs
di: Mou, Wenlong
Pubblicazione: (2025)

Optimal Rates for Robust Stochastic Convex Optimization
di: Gao, Changyu, et al.
Pubblicazione: (2024)

Finite-sample guarantees for data-driven forward-backward operator methods
di: Fabiani, Filippo, et al.
Pubblicazione: (2025)

Learning to accelerate Krasnosel'skii-Mann fixed-point iterations with guarantees
di: Martin, Andrea, et al.
Pubblicazione: (2026)

A stochastic gradient descent algorithm with random search directions
di: Gbaguidi, Eméric
Pubblicazione: (2025)

First-ish Order Methods: Hessian-aware Scalings of Gradient Descent
di: Smee, Oscar, et al.
Pubblicazione: (2025)

On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
di: Kwon, Jeongyeol, et al.
Pubblicazione: (2023)

A universal policy wrapper with guarantees
di: Bolychev, Anton, et al.
Pubblicazione: (2025)

Distributionally Robust Optimization with Adversarial Data Contamination
di: Li, Shuyao, et al.
Pubblicazione: (2025)

End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data
di: Chatzikiriakos, Nicolas, et al.
Pubblicazione: (2024)

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization
di: Akyildiz, Ömer Deniz, et al.
Pubblicazione: (2020)

Data-driven robust Markov decision processes on Borel spaces: performance guarantees via an axiomatic approach
di: Ramani, Sivaramakrishnan
Pubblicazione: (2026)

An inexact inertial projective splitting algorithm with strong convergence
di: Alves, M. Marques, et al.
Pubblicazione: (2025)

Stochastic global optimization of continuous functions via random walks on Grassmannians
di: Gupta, Kartik, et al.
Pubblicazione: (2026)