Results 151 to 160 of about 1,590,381 (357)
Journal of Inequalities and Applications, 2017 This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions.
Peiping Shen +2 more
doaj +1 more source
Bayesian stopping rules for multistart global optimization methods [PDF]
, 1987 C. G. E. Boender, A. H. G. Rinnooy Kan
openalex +1 more source
A Global Optimization Approach to Quantum Mechanics [PDF]
arXiv, 2006 This paper presents a global optimization approach to quantum mechanics, which describes the most fundamental dynamics of the universe. It suggests that the wave-like behavior of (sub)atomic particles could be the critical characteristic of a global optimization method deployed by nature so that (sub)atomic systems can find their ground states ...
arxiv
Learning to be Global Optimizer
, 2020 The advancement of artificial intelligence has cast a new light on the development of optimization algorithm. This paper proposes to learn a two-phase (including a minimization phase and an escaping phase) global optimization algorithm for smooth non-convex functions. For the minimization phase, a model-driven deep learning method is developed to learn
Zhang, Haotian +2 more
openaire +2 more sources
Globally Optimal Cooperation in Dense Cognitive Radio Networks [PDF]
arXiv, 2014 The problem of calculating the local and global decision thresholds in hard decisions based cooperative spectrum sensing is well known for its mathematical intractability. Previous work relied on simple suboptimal counting rules for decision fusion in order to avoid the exhaustive numerical search required for obtaining the optimal thresholds. However,
arxiv
, 2015 We consider the problem of global optimization of a function f from very noisy evaluations. We adopt a Bayesian sequential approach: evaluation points are chosen so as to reduce the uncertainty about the position of the global optimum of f, as measured ...
Aleksovska, Ivana +5 more
core +1 more source
Randomized directional search for nonconvex optimization [PDF]
arXivDirect search methods are a class of popular global optimization algorithms for general nonconvex programs. In this paper, we propose a randomized directional search algorithm (RDSA) for globally solving nonconvex optimization problems. The convergence of RDSA to a global optimizer is established and its computational complexity is derived ...
arxiv
Global optimization of statistical functions with simulated annealing [PDF]
, 1994 William L. Goffe +2 more
openalex +1 more source
Optimizing the Global Observational Network: A Dynamical Approach [PDF]
, 1993 C. Nicolis
openalex +1 more source
Multiple sclerosis clinical decision support system based on projection to reference datasets
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1863-1873, December 2022., 2022 Abstract Objective Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on‐demand computational power to address the challenges of dynamically managing MS. Methods A phase 3 clinical trial data (NCT00906399) were used to contextualize the medication efficacy of peg‐interferon beta‐1a vs ...
Chadia Ed‐driouch +13 more
wiley +1 more source