Results 61 to 70 of about 838,365 (209)
The bounds of feasible space on constrained nonconvex quadratic programming [PDF]
, 2008 This paper presents a method to estimate the bounds of the radius of the feasible space for a class of constrained nonconvex quadratic programmings. Results show that one may compute a bound of the radius of the feasible space by a linear programming ...
Zhu, Jinghao
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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 +3 more
wiley +1 more source
A note on set-semidefinite relaxations of nonconvex quadratic programs [PDF]
, 2013 We consider semidefinite, copositive, and more general, set-semidefinite programming relaxations of general nonconvex quadratic problems. For the semidefinite case a comparison between the feasible set of the original program and the feasible set of the ...
Ahmed, F., Still, Georg J.
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High Voltage, EarlyView.ABSTRACT With the development of electric power artificial intelligence (AI) technology, many complicated challenges emerged during application. Traditional AI algorithms work well in specialised tasks such as detection and classification. However, they are unlikely to solve general problems.
Yuanpeng Tan +4 more
wiley +1 more source
An ADMM-based heuristic algorithm for optimization problems over nonconvex second-order cone
Open Computer ScienceThe 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
Computing Skinning Weights via Convex Duality
Computer 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
Medial Axis Aware Learning of Signed Distance Functions
Computer Graphics Forum, EarlyView.Abstract We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump set of the gradient of the SDF, which coincides with the medial axis of the surface, is explicitly taken into account through a higher‐order variational formulation that enforces linear growth ...
Samuel Weidemaier +2 more
wiley +1 more source
Assessing second‐price auctions for parcel exchanges in last‐mile logistics
International Transactions in Operational Research, EarlyView.Abstract The rapid growth of e‐commerce has led to multiple carriers operating in the same regions, creating opportunities for collaboration. However, logistics companies typically operate independently, leading to inefficiencies. Horizontal cooperation, where carriers share resources and infrastructure, can improve efficiency and reduce costs.
Christian Truden, Margaretha Gansterer
wiley +1 more source
Performance Analysis of Optimization Methods in PSE Applications. Mathematical Programming Versus Grid-based Multi-parametric Genetic Algorithms [PDF]
, 2007 Due to their large variety of applications in the PSE area, complex optimisation problems are of high interest for the scientific community. As a consequence, a great effort is made for developing efficient solution techniques. The choice of the relevant
Ponsich, Antonin Sebastien +8 more
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The Reformulation-based aGO Algorithm for Solving Nonconvex MINLP Problems – Some Improvements
Chemical 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
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