Results 41 to 50 of about 969 (184)

Gaborlet‐guided sparse filtering: A novel intelligent method for lithology identification by vibration signals while drilling

Deep Underground Science and Engineering, EarlyView.
The flowchart illustrates rock specimen testing, vibration signal acquisition, and feature extraction with Gaborlet and sparse filtering for classification. Abstract Traditional lithology identification methods mainly rely on core sampling and well‐logging data.
Jian Hao, Danqi Zhang, Zhenqi Song, Jinrui Wang, Qi Wang, Heqing Liu   +5 more
wiley   +1 more source

The Barzilai and Borwein gradient method with nonmonotone line search for nonsmooth convex optimization problems

Mathematical Modelling and Analysis, 2012
The Barzilai and Borwein gradient algorithm has received a great deal of attention in recent decades since it is simple and effective for smooth optimization problems. Whether can it be extended to solve nonsmooth problems?
Gonglin Yuan, Zengxin Wei
doaj   +1 more source

Double‐Integration‐Enhanced Stochastic Gradient Descent Based on Neural Dynamics for Improving Generalisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Generalisation is a crucial aspect of deep learning, enabling models to perform well on unseen data. Currently, most optimisers that improve generalisation typically suffer from efficiency bottlenecks. This paper proposes a double‐integration‐enhanced stochastic gradient descent (DIESGD) optimiser, which treats the negative gradient as an ...
Ting Li, Longbang Wang, Jiexing Li, Jicheng Li   +3 more
wiley   +1 more source

Optimality and Duality Theorems in Nonsmooth Multiobjective Optimization [PDF]

Fixed Point Theory and Applications, 2011
Abstract In this paper, we consider a class of nonsmooth multiobjective programming problems. Necessary and sufficient optimality conditions are obtained under higher order strongly convexity for Lipschitz functions. We formulate Mond-Weir type dual problem and establish weak and strong duality theorems for a strict minimizer of order
Bae Kwan, Kim Do
openaire   +3 more sources

Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation

Computer Graphics Forum, EarlyView.
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley   +1 more source

Substantiation of the backpropagation technique via the Hamilton—Pontryagin formalism for training nonconvex nonsmooth neural networks

Доповiдi Нацiональної академiї наук України
The paper observes the similarity between the stochastic optimal control over discrete dynamical systems and the lear ning multilayer neural networks. It focuses on contemporary deep networks with nonconvex nonsmooth loss and activation functions.
V.I. Norkin
doaj   +1 more source

Mixed Super‐Circles

Computer Graphics Forum, EarlyView.
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, Thibaut Métivet, Florence Bertails‐Descoubes   +2 more
wiley   +1 more source

Random Carbon Tax Policy and Investment Into Emission Abatement Technologies

Mathematical Finance, EarlyView.
ABSTRACT We analyze the problem of a profit‐maximizing electricity producer, subject to carbon taxes, who decides on investments into CO2$\rm CO_2$ abatement technologies. We assume that the carbon tax policy is random and that the investment in the abatement technology is divisible, irreversible, and subject to transaction costs.
Katia Colaneri, Rüdiger Frey, Verena Köck   +2 more
wiley   +1 more source

Bregman iterative regularization using model functions for nonconvex nonsmooth optimization

Frontiers in Applied Mathematics and Statistics, 2022
In this paper, we propose a new algorithm called ModelBI by blending the Bregman iterative regularization method and the model function technique for solving a class of nonconvex nonsmooth optimization problems.
Haoxing Yang, Hui Zhang, Hongxia Wang, Lizhi Cheng   +3 more
doaj   +1 more source

A novel dual‐decomposition method for non‐convex two‐stage stochastic mixed‐integer quadratically constrained quadratic problems

International Transactions in Operational Research, Volume 33, Issue 5, Page 3128-3157, September 2026.
Abstract We propose the novel p‐branch‐and‐bound method for solving two‐stage stochastic programming problems whose deterministic equivalents are represented by non‐convex mixed‐integer quadratically constrained quadratic programming (MIQCQP) models. The precision of the solution generated by the p‐branch‐and‐bound method can be arbitrarily adjusted by
Nikita Belyak, Fabricio Oliveira
wiley   +1 more source