Results 151 to 160 of about 463,836 (293)

A Combined Quasi-Newton-Type Method Using 4th-Order Directional Derivatives for Solving Degenerate Problems of Unconstrained Optimization

Кібернетика та комп'ютерні технології
Introduction. Methods of unconstrained optimization play a significant role in machine learning [1–6]. When solving practical problems in machine learning, such as tuning nonlinear regression models, the extremum point of the chosen optimality criterion ...
Viktor Zadachyn
doaj   +1 more source

Exploring market dynamics of biological including biosimilar treatments for retinal diseases in Europe: An interrupted time‐series analysis

Acta Ophthalmologica, EarlyView.
Abstract Purpose To assess the impact of biosimilar ranibizumab and on‐patent faricimab market entry on pricing and utilization trends and describe national variation in off‐label bevacizumab use in Europe. Methods Interrupted time series analysis of quarterly sales data (Q1 2018–Q2 2024) in 11 European countries evaluated ranibizumab utilization and ...
Elif Car, Isabelle Huys, Steven Simoens, Arnold G. Vulto   +3 more
wiley   +1 more source

Properties and Application of Incomplete Orthogonalization in the Directions of Gradient Difference in Optimization Methods

Mathematics
This paper considers the problem of unconstrained minimization of smooth functions. Despite the high efficiency of quasi-Newton methods such as BFGS, their performance degrades in ill-conditioned problems with unstable or rapidly varying Hessians—for ...
Vladimir Krutikov, Elena Tovbis, Svetlana Gutova, Ivan Rozhnov, Lev Kazakovtsev   +4 more
doaj   +1 more source

Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation

Computer Graphics Forum, EarlyView.
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley   +1 more source

Mesh Processing Non‐Meshes via Neural Displacement Fields

Computer Graphics Forum, EarlyView.
Abstract Mesh processing pipelines are mature, but adapting them to newer non‐mesh surface representations—which enable fast rendering with compact file size—requires costly meshing or transmitting bulky meshes, negating their core benefits for streaming applications.
Yuta Noma, Zhecheng Wang, Chenxi Liu, Karan Singh, Alec Jacobson   +4 more
wiley   +1 more source

Progressively Projected Newton's Method

Computer Graphics Forum, EarlyView.
Abstract Newton's Method is widely used to find the solution of complex non‐linear simulation problems. To guarantee a descent direction, it is common practice to clamp the negative eigenvalues of each element Hessian prior to assembly—a strategy known as Projected Newton (PN)—but this perturbation often hinders convergence.
J. A. Fernández‐Fernández, F. Löschner, J. Bender   +2 more
wiley   +1 more source

Memoryless quasi-Newton-type methods via some weak secant relations for large-scale unconstrained optimization

Journal of Inequalities and Applications
This article presents two variants of memoryless quasi-Newton methods with backtracking line search for large-scale unconstrained minimization. These updating methods are derived by means of a least-change updating strategy subjected to some weaker form ...
Keat Hee Lim, Wah June Leong
doaj   +1 more source

Skeletal‐Driven Animation of Anatomical Humans via Neural Deformation Gradients

Computer Graphics Forum, EarlyView.
Abstract Most real‐time animation techniques for digital humans are limited to deforming the outer skin surface. Geometric skinning methods are highly efficient but struggle with artifacts such as collapsing joints or self‐intersections when animating inner anatomy along with the outer skin.
G. Nolte, F. Kemper, U. Schwanecke, M. Botsch   +3 more
wiley   +1 more source

Hierarchical Optimization of the As‐Rigid‐As‐Possible Energy

Computer Graphics Forum, EarlyView.
Abstract The As‐Rigid‐As‐Possible (ARAP) energy [SA07] has become a versatile ingredient in various geometry processing and machine learning methods. The classic method for its minimization is a block coordinate descent, alternating between local rotation estimation and a global linear solve, which converges slowly for large problem instances.
Hendrik Meyer, Bernd Bickel, Marc Alexa
wiley   +1 more source

Mixed Super‐Circles

Computer Graphics Forum, EarlyView.
Abstract We introduce mixed super‐circles, a position‐curvature formulation of the original dynamic 2D super‐helix model. Compared to the latter, purely curvature‐based model – the so‐called chained formulation –, the mixed formulation that we propose here drastically reduces the algorithmic complexity of the solving scheme – from quadratic to quasi ...
Emile Hohnadel, Thibaut Métivet, Florence Bertails‐Descoubes   +2 more
wiley   +1 more source