«gradient algorithm»
۲۳٬۳۹۵ نتیجهImplementation of the Conjugate Gradient Algorithm in DSO
Computation of the inner state parameters in DSO inversion requires solving a large normal matrix system. A combined conjugate gradient and Lanczos iterative technique can be used to both solve the system and approximate some of the spectrum of the normal operator. At each iterat
A New Perspective of Proximal Gradient Algorithms
We provide a new perspective to understand proximal gradient algorithms. We show that both proximal gradient algorithm (PGA) and Bregman proximal gradient algorithm (BPGA) can be viewed as generalized proximal point algorithm (GPPA), based on which more accurate convergence rates
A Dai-Yuan conjugate gradient algorithm with sufficient descent and conjugacy conditions for unconstrained optimization
A modification of the Dai-Yuan conjugate gradient algorithm is proposed. Using the exact line search, the algorithm reduces to the original version of the Dai and Yuan computational scheme. For inexact line search the algorithm satisfies both the sufficient descent and conjugacy
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the estimate of the gradient. In this paper, we formulate the variance reduction problem by describing a s
Conjugate Gradient Algorithm for Optimization Under Unitary Matrix Constraint1
In this paper we introduce a Riemannian algorithm for minimizing (or maximizing) a real-valued function J of complex-valued matrix argument W under the constraint that W is an n × n unitary matrix. This type of constrained optimization problem arises in many array and multi-chann
Proximal gradient algorithm for group sparse optimization
In this paper, we propose a proximal gradient algorithm for solving a general nonconvex and nonsmooth optimization model of minimizing the summation of a C1,1 function and a grouped separable lsc function. This model includes the group sparse optimization via lp,q regularization
A modified Polak-Ribière-Polyak conjugate gradient algorithm for unconstrained optimization
A modified Polak-Ribière-Polyak conjugate gradient algorithm which satisfies both the sufficient descent condition and the conjugacy condition is presented. These properties are independent of the line search. The algorithms use the standard Wolfe line search. Under standard assu
Preconditioned Hybrid Conjugate Gradient Algorithm for P-laplacian
In this paper, a hybrid conjugate gradient algorithm with weighted preconditioner is proposed. The algorithm can efficiently solve the minimizing problem of general function deriving from finite element discretization of the p-Laplacian. The algorithm is efficient, and its conver
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems
The proximal gradient algorithm has been popularly used for convex optimization. Recently, it has also been extended for nonconvex problems, and the current state-of-the-art is the nonmonotone accelerated proximal gradient algorithm. However, it typically requires two exact proxi
carotid artery wall motion estimation from consecutive ultrasonic images: comparison between block-matching and maximum-gradient algorithms
background: radial movement of the arterial wall is a well-known indicator of the mechanical properties of arteries in arterial disease examinations. in the present study, two different motion estimation methods, based on the block-matching and maximum-gradient algorithms, were e