Results 31 to 40 of about 30,326 (205)
Nonsmooth analysis and approximation
Journal of Approximation Theory, 1988 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Κανδυλακης Δημητριος(http://users.isc.tuc.gr/~dkandylakis) +2 more
openaire +3 more sources
Multiplicity of nontrivial solutions for elliptic equations with nonsmooth potential and resonance at higher eigenvalues [PDF]
, 2006 We consider a semilinear elliptic equation with a nonsmooth, locally \hbox{Lipschitz} potential function (hemivariational inequality). Our hypotheses permit double resonance at infinity and at zero (double-double resonance situation).
Gasi'nski, Leszek +2 more
core +1 more source
Nonsmooth analysis approach to Isaac's equation
International Journal of Mathematics and Mathematical Sciences, 1993 We study Isaacs' equation (∗)wt(t,x)+H(t,x,wx(t,x))=0 (H is a highly nonlinear function) whose natural solution is a value W(t,x) of a suitable differential game.
Leszek S. Zaremba
doaj +1 more source
Higher-order error bound for the difference of two functions
Journal of Inequalities and Applications, 2018 Error bounds play an important role in the research of mathematical programming. Using some techniques of nonsmooth analysis, we establish some results on the existence of higher-order error bounds for difference functions with set constraints.
Hui Huang, Mengxue Xia
doaj +1 more source
IEEE Access, 2022 Quaternions have appeared in many practical fields, such as image processing and data mining, and so on. This paper focuses on designing an efficient quaternion-valued neurodynamic approach (QNA) based on multi-agent systems to solve nonsmooth convex ...
Guocheng Li +3 more
doaj +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Generalized Newton's Method based on Graphical Derivatives [PDF]
, 2010 This paper concerns developing a numerical method of the Newton type to solve systems of nonlinear equations described by nonsmooth continuous functions. We propose and justify a new generalized Newton algorithm based on graphical derivatives, which have
Hoheisel, T. +3 more
core +2 more sources
Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees
, 2020 Asynchronous distributed algorithms are a popular way to reduce synchronization costs in large-scale optimization, and in particular for neural network training.
Alistarh, Dan +3 more
core +2 more sources
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Semiactive Nonsmooth Control for Building Structure with Deep Learning
Complexity, 2017 Aiming at suppressing harmful effect for building structure by surface motion, semiactive nonsmooth control algorithm with Deep Learning is proposed. By finite-time stable theory, the building structure closed-loop system’s stability is discussed under ...
Qing Wang +3 more
doaj +1 more source