Results 61 to 70 of about 24,807 (199)

Catalyst Acceleration for Gradient-Based Non-Convex Optimization [PDF]

open access: yes, 2017
We introduce a generic scheme to solve nonconvex optimization problems using gradient-based algorithms originally designed for minimizing convex functions.
Drusvyatskiy, Dmitriy   +4 more
core   +1 more source

Computing Skinning Weights via Convex Duality

open access: yesComputer Graphics Forum, EarlyView.
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley   +1 more source

The Reformulation-based aGO Algorithm for Solving Nonconvex MINLP Problems – Some Improvements

open access: yesChemical Engineering Transactions, 2013
The a-reformulation (aR) technique can be used to transform any nonconvex twice-differentiable mixed-integer nonlinear programming problem to a convex relaxed form.
A. Lundell, T. Westerlund
doaj   +1 more source

Sequential Convex Programming Methods for Solving Nonlinear Optimization Problems with DC constraints [PDF]

open access: yes, 2011
This paper investigates the relation between sequential convex programming (SCP) as, e.g., defined in [24] and DC (difference of two convex functions) programming.
Diehl, Moritz, Quoc, Tran Dinh
core  

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

open access: yesAIChE Journal, Volume 72, Issue 6, June 2026.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman   +3 more
wiley   +1 more source

An ADMM-based heuristic algorithm for optimization problems over nonconvex second-order cone

open access: yesOpen Computer Science
The nonconvex second-order cone (nonconvex SOC) is a nonconvex extension to the convex second-order cone, in the sense that it consists of any vector divided into two sub-vectors for which the Euclidean norm of the first sub-vector is at least as large ...
Alzalg Baha, Benakkouche Lilia
doaj   +1 more source

Energy Efficiency Beamforming Design for UAV Communications With Broadband Hybrid Polarization Antenna Arrays

open access: yesIEEE Access, 2019
Stringent physical resource constraints in unmanned aerial vehicle (UAV) communications bring new challenges to energy efficient transmission. In this paper, we study energy efficient beamforming for UAV communications, where a wideband hybrid polarized ...
Gui Zhou
doaj   +1 more source

Diffusion model‐regularized implicit neural representation for computed tomography metal artifact reduction

open access: yesQuantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Computed tomography (CT) images are often severely corrupted by artifacts in the presence of metals. Existing supervised metal artifact reduction (MAR) approaches suffer from performance instability on known data due to their reliance on limited paired metal‐clean data, which limits their clinical applicability. Moreover, existing unsupervised
Jie Wen   +3 more
wiley   +1 more source

On the Foundational Arguments of Sufficient Dimension Reduction

open access: yesWIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

open access: yesAIChE Journal, Volume 72, Issue 5, May 2026.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed   +4 more
wiley   +1 more source

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