Results 131 to 140 of about 124,946 (301)
Mesh Processing Non‐Meshes via Neural Displacement Fields
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 +4 more
wiley +1 more source
Quasi-Newton methods with provable efficiency guarantees
Quasi-Newton methods are very popular in Optimization. They have a long, rich history, and perform extremely well for solving real-life problems. However, almost nothing is known about theoretical efficiency guarantees for these methods. The goal of this
Rodomanov, Anton
core
Progressively Projected Newton's Method
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 +2 more
wiley +1 more source
A Hybrid of Quasi-Newton Method with CG Method for Unconstrained Optimization
The quasi-Newton is a well-known method for solving small to medium-scale unconstrained optimization problems due to its simplicity and convergence. This leads to many modifications to improve its performance, and one of them is by hybridizing it with ...
Sulaiman, I.M +3 more
core
A new smoothing quasi-Newton method for nonlinear complementarity problems
A new smoothing quasi-Newton method for nonlinear complementarity problems is presented. The method is a generalization of Thomas’ method for smooth nonlinear systems and has similar properties as Broyden's method.
Krejić, Nataša, Buhmiler, Sandra
core +1 more source
Skeletal‐Driven Animation of Anatomical Humans via Neural Deformation Gradients
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 +3 more
wiley +1 more source
Hierarchical Optimization of the As‐Rigid‐As‐Possible Energy
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
A Quasi-Newton Trust-Region Method
The classical trust-region method for unconstrained minimization can be augmented with a line search that finds a point that satisfies the Wolfe conditions. One can use this new method to define an algorithm that simultaneously satisfies the quasi-Newton
E. Michael Gertz
core
It is well known that the conjugate gradient method and a quasi-Newton method, using any well-defined update matrix from the one-parameter Broyden family of up- dates, produce identical iterates on a quadratic problem with positive definite Hessian. This
Anders Forsgren +5 more
core +1 more source
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 +2 more
wiley +1 more source

