Cover Image

Fitting ARMA Time Series Models without Identification: A Proximal Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Yin, Tajbakhsh, Sam Davanloo
Format:	Preprint
Published:	2020
Subjects:	Computation Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Stochastic Optimization Algorithms for Problems with Controllable Biased Oracles
by: Liu, Yin, et al.
Published: (2023)

Nonasymptotic Analysis of Accelerated Methods With Inexact Oracle Under Absolute Error Bound
by: Liu, Yin, et al.
Published: (2024)

Riemannian Stochastic Gradient Method for Nested Composition Optimization
by: Zhang, Dewei, et al.
Published: (2022)

Identification of High-Dimensional ARMA Models with Binary-Valued Observations
by: Li, Xin, et al.
Published: (2024)

Discovering Mechanistic Causality from Time Series: A Behavioral-System Approach
by: Liu, Yingzhu, et al.
Published: (2025)

Relaxed Proximal Point Algorithm: Tight Complexity Bounds and Acceleration without Momentum
by: Wang, Bofan, et al.
Published: (2024)

An Accelerated Proximal Bundle Method with Momentum
by: Zheng, Zhuoqing, et al.
Published: (2026)

Proximal gradient-type method with generalized distance and convergence analysis without global descent lemma
by: Yagishita, Shotaro, et al.
Published: (2025)

Sink Proximity: A Novel Approach for Online Vehicle Dispatch in Ride-hailing
by: Wang, Ruiting, et al.
Published: (2025)

A Unified Theory of Stochastic Proximal Point Methods without Smoothness
by: Richtárik, Peter, et al.
Published: (2024)

Proximal Interacting Particle Langevin Algorithms
by: Encinar, Paula Cordero, et al.
Published: (2024)

Convergence of Nonmonotone Proximal Gradient Methods under the Kurdyka-Lojasiewicz Property without a Global Lipschitz Assumption
by: Kanzow, Christian, et al.
Published: (2024)

Variational Analysis of Proximal Compositions and Integral Proximal Mixtures
by: Combettes, Patrick L., et al.
Published: (2024)

Revisiting Atomic Norm Minimization: A Sequential Approach for Atom Identification and Refinement
by: Liu, Xiaozhi, et al.
Published: (2024)

A Dynamic Mode Decomposition Approach to Parameter Identification
by: Abudia, Moad, et al.
Published: (2026)

A Riemannian Proximal Newton Method
by: Si, Wutao, et al.
Published: (2023)

An Inexact Preconditioned Zeroth-order Proximal Method for Composite Optimization
by: Liu, Shanglin, et al.
Published: (2024)

Anisotropic Proximal Gradient
by: Laude, Emanuel, et al.
Published: (2022)

An Unconstrained Optimization Approach to Moment Fitting with Phase Type Distributions
by: Sherzer, Eliran, et al.
Published: (2025)

Proximal methods for point source localisation
by: Valkonen, Tuomo
Published: (2022)

Proximal Comixture Minimization Models for Image Recovery and Data Analysis
by: Combettes, Patrick L., et al.
Published: (2024)

A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds
by: Wang, Lei, et al.
Published: (2024)

From Time Series to Affine Systems
by: Padoan, A., et al.
Published: (2025)

Safe Feature Identification Rule for Fused Lasso by An Extra Dual Variable
by: Shang, Pan, et al.
Published: (2024)

A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems
by: Wang, Qingsong, et al.
Published: (2024)

A Riemannian Proximal Newton-CG Method
by: Huang, Wen, et al.
Published: (2024)

Anisotropic Proximal Point Algorithm
by: Laude, Emanuel, et al.
Published: (2023)

On the Acceleration of Proximal Bundle Methods
by: Fersztand, David, et al.
Published: (2025)

Mirror-Free Proximal Methods
by: Vyas, Abhijeet, et al.
Published: (2026)

Continuation Method for Nonsmooth Model Predictive Control Using Proximal Technique
by: Shima, Ryotaro, et al.
Published: (2024)

Proximal-Based Generative Modeling for Bayesian Inverse Problems
by: Zhang, Boyang, et al.
Published: (2026)

Proximal observers for secure state estimation
by: Bako, Laurent, et al.
Published: (2024)

An Inexact Proximal Framework for Nonsmooth Riemannian Difference-of-Convex Optimization
by: Jiang, Bo, et al.
Published: (2025)

Parallel and Proximal Constrained Linear-Quadratic Methods for Real-Time Nonlinear MPC
by: Jallet, Wilson, et al.
Published: (2024)

A Proximal Descent Method for Minimizing Weakly Convex Optimization
by: Liao, Feng-Yi, et al.
Published: (2025)

La Méthode du Gradient Proximé
by: Combettes, Patrick L.
Published: (2025)

Proximal gradient methods beyond monotony
by: De Marchi, Alberto
Published: (2022)

Proximal gradient methods in Banach spaces
by: Wachsmuth, Gerd, et al.
Published: (2025)

Exploiting Multistage Optimization Structure in Proximal Solvers
by: Schwan, Roland, et al.
Published: (2025)

Solving The Dynamic Volatility Fitting Problem: A Deep Reinforcement Learning Approach
by: Gnabeyeu, Emmanuel, et al.
Published: (2024)