Results 51 to 60 of about 50,039 (279)
Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem
, 2017 We propose a new algorithm for sparse estimation of eigenvectors in generalized eigenvalue problems (GEP). The GEP arises in a number of modern data-analytic situations and statistical methods, including principal component analysis (PCA), multiclass ...
Anant Agrawal (3953690) +6 more
core +3 more sources
Shape optimization in contact problems based on penalization of the state inequality [PDF]
Applications of Mathematics, 1986 The paper deals with the frictionless plane contact problem of a linear- elastic sheet resting on a rigid foundation. The shape optimization is carried out in such a manner that the contact boundary curve \(\alpha\) should be the result of the minimization of the total potential energy with respect to \(\alpha\), the contact problem being described by ...
Haslinger, Jaroslav +2 more
openaire +2 more sources
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Multi-Attribute Graph Estimation With Sparse-Group Non-Convex Penalties
IEEE AccessWe consider the problem of inferring the conditional independence graph (CIG) of high-dimensional Gaussian vectors from multi-attribute data. Most existing methods for graph estimation are based on single-attribute models where one associates a scalar ...
Jitendra K. Tugnait
doaj +1 more source
A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials
Advanced Engineering Materials, EarlyView.This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline +2 more
wiley +1 more source
AIP Advances, 2023 An optimization method combining deep reinforcement learning (DRL) and computational fluid dynamics (CFD) was developed, and its effectiveness and limitations are investigated.
T. Noda +4 more
doaj +1 more source
Communication-Efficient Distributed Learning for High-Dimensional Support Vector Machines
Mathematics, 2022 Distributed learning has received increasing attention in recent years and is a special need for the era of big data. For a support vector machine (SVM), a powerful binary classification tool, we proposed a novel efficient distributed sparse learning ...
Xingcai Zhou, Hao Shen
doaj +1 more source
On the properties of the solution path of the constrained and penalized L2-L0 problems [PDF]
, 2009 12 pagesTechnical report on the properties of the L0-constrained least-square minimization problem and the L0-penalized least-square minimization problem: domain of optimization, notion of solution path, properties of the "penalized" solution path..
Brie, David +3 more
core +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Limit analysis and inf-sup conditions on convex cones [PDF]
, 2019 This paper is focused on analysis and reliable computations of limit loads in perfect plasticity. We recapitulate our recent results arising from a continuous setting of the so-called limit analysis problem.
Haslinger, Jaroslav +2 more
core