Zobrazeno 1 - 10
of 4 802
pro vyhledávání: '"WANG, Hongxia"'
The Bundle Adjustment (BA) model is commonly optimized using a nonlinear least squares method, with the Levenberg-Marquardt (L-M) algorithm being a typical choice. However, despite the L-M algorithm's effectiveness, its sensitivity to initial conditi
Externí odkaz:
http://arxiv.org/abs/2411.06343
Gradient descent methods are fundamental first-order optimization algorithms in both Euclidean spaces and Riemannian manifolds. However, the exact gradient is not readily available in many scenarios. This paper proposes a novel inexact Riemannian gra
Externí odkaz:
http://arxiv.org/abs/2409.11181
Transition videos play a crucial role in media production, enhancing the flow and coherence of visual narratives. Traditional methods like morphing often lack artistic appeal and require specialized skills, limiting their effectiveness. Recent advanc
Externí odkaz:
http://arxiv.org/abs/2408.13413
Autor:
Zhang, Shuchang, Wang, Hongxia
In recent years Plug-and-Play (PnP) methods have achieved state-of-the-art performance in inverse imaging problems by replacing proximal operators with denoisers. Based on the proximal gradient method, some theoretical results of PnP have appeared, w
Externí odkaz:
http://arxiv.org/abs/2408.12100
Preconditioned Proximal Point (PPP) algorithms provide a unified framework for splitting methods in image restoration. Recent advancements with RED (Regularization by Denoising) and PnP (Plug-and-Play) priors have achieved state-of-the-art performanc
Externí odkaz:
http://arxiv.org/abs/2407.13120
The derivative-free projection method (DFPM) is an efficient algorithm for solving monotone nonlinear equations. As problems grow larger, there is a strong demand for speeding up the convergence of DFPM. This paper considers the application of Anders
Externí odkaz:
http://arxiv.org/abs/2403.14924
This paper proposes several novel optimization algorithms for minimizing a nonlinear objective function. The algorithms are enlightened by the optimal state trajectory of an optimal control problem closely related to the minimized objective function.
Externí odkaz:
http://arxiv.org/abs/2403.11115
We propose and analyze a general framework called nonlinear preconditioned primal-dual with projection for solving nonconvex-nonconcave and non-smooth saddle-point problems. The framework consists of two steps. The first is a nonlinear preconditioned
Externí odkaz:
http://arxiv.org/abs/2401.05143
Autor:
Zhang, Huanshui, Wang, Hongxia
In the paper, we propose solving optimization problems (OPs) and understanding the Newton method from the optimal control view. We propose a new optimization algorithm based on the optimal control problem (OCP). The algorithm features converging more
Externí odkaz:
http://arxiv.org/abs/2312.01334