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In this paper, we propose new methods to efficiently solve convex optimization problems encountered in sparse estimation, which include a new quasi-Newton method that avoids computing the Hessian matrix and improves efficiency, and we prove…

Optimization and Control · Mathematics 2023-09-06 Ryosuke Shimmura , Joe Suzuki

We address the problem of accelerating thin-shell deformable object simulations by dimension reduction. We present a new algorithm to embed a high-dimensional configuration space of deformable objects in a low-dimensional feature space,…

Graphics · Computer Science 2020-03-02 Qingyang Tan , Zherong Pan , Lin Gao , Dinesh Manocha

Machine learning (ML) problems are often posed as highly nonlinear and nonconvex unconstrained optimization problems. Methods for solving ML problems based on stochastic gradient descent are easily scaled for very large problems but may…

Numerical Analysis · Mathematics 2019-05-24 Jennifer B. Erway , Joshua Griffin , Roummel F. Marcia , Riadh Omheni

The question of how to incorporate curvature information in stochastic approximation methods is challenging. The direct application of classical quasi- Newton updating techniques for deterministic optimization leads to noisy curvature…

Optimization and Control · Mathematics 2015-02-19 R. H. Byrd , S. L. Hansen , J. Nocedal , Y. Singer

The field of optimal design of linear elastic structures has seen many exciting successes that resulted in new architected materials and structural designs. With the availability of cloud computing, including high-performance computing,…

Computational Engineering, Finance, and Science · Computer Science 2021-02-09 Diab W. Abueidda , Seid Koric , Nahil A. Sobh

Deep learning algorithms often require solving a highly non-linear and nonconvex unconstrained optimization problem. Methods for solving optimization problems in large-scale machine learning, such as deep learning and deep reinforcement…

Machine Learning · Computer Science 2019-09-06 Jacob Rafati , Roummel F. Marcia

We present novel coupling schemes for partitioned multi-physics simulation that combine four important aspects for strongly coupled problems: implicit coupling per time step, fast and robust acceleration of the corresponding iterative…

Numerical Analysis · Mathematics 2020-09-21 Benjamin Rüth , Benjamin Uekermann , Miriam Mehl , Philipp Birken , Azahar Monge , Hans-Joachim Bungartz

Finite elasticity problems commonly include material and geometric nonlinearities and are solved using various numerical methods. However, for highly nonlinear problems, achieving convergence is relatively difficult and requires small load…

Numerical Analysis · Mathematics 2018-05-01 Yue Mei , Daniel E. Hurtado , Sanjay Pant , Ankush Aggarwal

This work proposes a model-reduction approach for the material point method on nonlinear manifolds. Our technique approximates the $\textit{kinematics}$ by approximating the deformation map using an implicit neural representation that…

Machine Learning · Computer Science 2023-02-13 Peter Yichen Chen , Maurizio M. Chiaramonte , Eitan Grinspun , Kevin Carlberg

This work considers the application of the virtual element method to plane hyperelasticity problems with a novel approach to the selection of stabilization parameters. The method is applied to a range of numerical examples and well known…

Numerical Analysis · Mathematics 2020-06-24 Daniel van Huyssteen , Batmanathan Dayanand Reddy

Simulation of human soft tissues in contact with their environment is essential in many fields, including visual effects and apparel design. Biological tissues are nearly incompressible. However, standard methods employ compressible…

Graphics · Computer Science 2021-09-06 Seung Heon Sheen , Egor Larionov , Dinesh K. Pai

The position-based dynamics (PBD) algorithm is a popular and versatile technique for real-time simulation of deformable bodies, but is only applicable to forces that can be expressed as linearly compliant constraints. In this work, we…

Graphics · Computer Science 2025-12-01 Manas Chaudhary , Chandradeep Pokhariya , Rahul Narain

Four decades after their invention, quasi-Newton methods are still state of the art in unconstrained numerical optimization. Although not usually interpreted thus, these are learning algorithms that fit a local quadratic approximation to…

Numerical Analysis · Computer Science 2012-06-22 Philipp Hennig , Martin Kiefel

The finite element method (FEM) is among the most commonly used numerical methods for solving engineering problems. Due to its computational cost, various ideas have been introduced to reduce computation times, such as domain decomposition,…

Computational Engineering, Finance, and Science · Computer Science 2019-11-07 Andrea Mendizabal , Pablo Márquez-Neila , Stéphane Cotin

Hessian information speeds convergence substantially in motion optimization. The better the Hessian approximation the better the convergence. But how good is a given approximation theoretically? How much are we losing? This paper addresses…

Robotics · Computer Science 2016-05-31 Nathan Ratliff , Marc Toussaint , Jeannette Bohg , Stefan Schaal

Lattice models are popular methods for simulating deformation of solids by discretizing continuum structures into spring networks. Despite the simplicity and efficiency, most lattice models only rigorously converge to continuum models for…

Soft Condensed Matter · Physics 2018-09-10 Teng Zhang

Materials used in real clothing exhibit remarkable complexity and spatial variation due to common processes such as stitching, hemming, dyeing, printing, padding, and bonding. Simulating these materials, for instance using finite element…

In this paper, we extend and investigate the properties of the semi-smooth Newton method when applied to a general projection equation in finite dimensional spaces. We first present results concerning Clarke's generalized Jacobian of the…

Optimization and Control · Mathematics 2024-01-10 Nicolas F. Armijo , Yunier Bello-Cruz , Gabriel Haeser

With the growing maturity of additive manufacturing, the fabrication of architected or lattice-based metamaterials has become a reality for industrial applications. These materials combine lightweight design with tailored mechanical…

Numerical Analysis · Mathematics 2026-03-12 Clément Guillet , Thibaut Hirschler , Pierre Jolivet , Pablo Antolin , Robin Bouclier

We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of…

Materials Science · Physics 2026-02-17 Artem Chuprov , Egor E. Nuzhin , Alexey A. Tsukanov , Nikolay V. Brilliantov