Results 31 to 40 of about 214,384,274 (154)
Animal Genetics, Volume 57, Issue 6, December 2026.ABSTRACT Generative adversarial networks (GANs) are artificial intelligence models designed to generate novel data that is indistinguishable from real data. Originally developed to generate images to complement existing datasets and create more diverse samples, GAN‐based data can enhance downstream analysis for machine learning and deep learning ...
Edgar Caballero Vargas, Tiago Bresolin
wiley +1 more source
Electronic Journal of Differential Equations, 1998 Summary: We apply the minmax principle we developed in [\textit{A. Castro, J. Cossio} and \textit{J. M. Neuberger}, Rocky Mt. J. Math. 27, No. 4, 1041-1053 (1997)]\ to obtain sign-changing solutions for superlinear and asymptotically linear Dirichlet problems. We prove that, when isolated, the local degree of any solution given by this minmax principle
Castro, Alfonso +2 more
openaire +2 more sources
Social Exchange and Reciprocal Integration Between Migrants and Locals at Work
Human Resource Management Journal, Volume 36, Issue 4, Page 813-828, November 2026.ABSTRACT Workplaces are pivotal “contact zones” where migrants and locals negotiate access to jobs, resources, and recognition, yet HRM research has rarely examined how everyday encounters generate integrated relationships at work. This conceptual paper introduces reciprocal integration as a workplace‐anchored social exchange process: the emergent ...
Minna Paunova, Maribel Blasco
wiley +1 more source
Generic singularities of minimax solutions to Hamilton--Jacobi equations [PDF]
, 2004 Minimax solutions are weak solutions to Cauchy problems involving Hamilton--Jacobi equations, constructed from generating families quadratic at infinity of their geometric solutions.
Capitanio, Gianmarco
core +2 more sources
A Note on Local Polynomial Regression for Time Series in Banach Spaces
Journal of Time Series Analysis, Volume 47, Issue 6, Page 1124-1138, November 2026.ABSTRACT This work extends local polynomial regression to Banach space‐valued time series for estimating smoothly varying means and their derivatives in non‐stationary data. The asymptotic properties of both the standard and bias‐reduced Jackknife estimators are analyzed under mild moment conditions, establishing their convergence rates.
Florian Heinrichs
wiley +1 more source
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
Advanced Intelligent Systems, Volume 8, Issue 10, October 2026.A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
Re-Aggregation Heuristics for the Large Location Problems with Lexicographic Minimax Objective
, 2015 We propose a new heuristic algorithm that provides solutions to the discrete lexicographic minimax location problem. The algorithm is applicable to large instances of the problem.
Lubos Buzna, Matej Cebecauer
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Nontrivial solutions for nonlinear elliptic problems via Morse theory
Electronic Journal of Differential Equations, 2006 We prove the existence of nontrivial solutions for perturbations of p-Laplacian. Our approach combine minimax arguments and Morse Theory, under the conditions on the behaviors of the perturbed function $f(x,t)$ or its primitive $F(x,t)$ near infinity and
Abdesslem Ayoujil, Abdel R. El Amrouss
doaj
On the existence of solutions to adversarial training in multiclass classification
European Journal of Applied MathematicsAdversarial training is a min-max optimization problem that is designed to construct robust classifiers against adversarial perturbations of data. We study three models of adversarial training in the multiclass agnostic-classifier setting.
Nicolás García Trillos +2 more
doaj +1 more source
Engineering Reports, Volume 8, Issue 10, October 2026.This paper reviews recent advances in hybrid deep learning for intelligent fault diagnosis of rotating machinery, focusing on GAN‐ and CNN‐based architectures and their specialized variants. Hybrid GAN‐CNN methods are categorized into three groups: (1) optimized original GANs with CNN variants, (2) improved GAN architectures integrated with CNNs, and ...
Temesgen Tadesse Feisa +7 more
wiley +1 more source