Zobrazeno 1 - 10
of 378
pro vyhledávání: '"Gould, Nicholas"'
Autor:
Joslyn, Cliff, Charles, Lauren, DePerno, Chris, Gould, Nicholas, Nowak, Kathleen, Praggastis, Brenda, Purvine, Emilie, Robinson, Michael, Strules, Jennifer, Whitney, Paul
Integration of heterogeneous sensors is a challenging problem across a range of applications. Prominent among these are multi-target tracking, where one must combine observations from different sensor types in a meaningful way to track multiple targe
Externí odkaz:
http://arxiv.org/abs/1912.05487
Autor:
Badgett, Samantha L., Scheible, Melissa K.R., Livingston, Isabella G., Meredith, Erin P., Gould, Nicholas P., Strules, Jennifer, DePerno, Christopher S., Olfenbuttel, Colleen, Stoskopf, Michael K., Breen, Matthew, Arnold, Chad, Meiklejohn, Kelly A.
Publikováno v:
In Forensic Science International: Animals and Environments December 2023 4
Adaptive cubic regularization methods have emerged as a credible alternative to linesearch and trust-region for smooth nonconvex optimization, with optimal complexity amongst second-order methods. Here we consider a general/new class of adaptive regu
Externí odkaz:
http://arxiv.org/abs/1811.07057
Publikováno v:
Optimization methods and Software, vol. 35(2), pp. 243-256, 2020
The unconstrained minimization of a sufficiently smooth objective function $f(x)$ is considered, for which derivatives up to order $p$, $p\geq 2$, are assumed to be available. An adaptive regularization algorithm is proposed that uses Taylor models o
Externí odkaz:
http://arxiv.org/abs/1708.04044
Publikováno v:
Numerical Algorithms; Aug2024, Vol. 96 Issue 4, p1675-1698, 24p
Autor:
Gould, Nicholas Mark
This thesis proposes that on-demand mapping - where the user can choose the geographic features to map and the scale at which to map them - can be supported by formalising, and making explicit, cartographic generalisation knowledge in an ontology. Th
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.634976
Autor:
Packwood, David, Kermode, James, Mones, Letif, Bernstein, Noam, Woolley, John, Gould, Nicholas, Ortner, Christoph, Csanyi, Gabor
Publikováno v:
J. Chem. Phys. 144, 164109 (2016)
We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonst
Externí odkaz:
http://arxiv.org/abs/1604.02570
Publikováno v:
Optimization Methods and Software, 31(1):157-186, 2016
In this paper, we consider augmented Lagrangian (AL) algorithms for solving large-scale nonlinear optimization problems that execute adaptive strategies for updating the penalty parameter. Our work is motivated by the recently proposed adaptive AL tr
Externí odkaz:
http://arxiv.org/abs/1408.4500
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