Results 41 to 50 of about 7,447,344 (290)
Machine Learning in Quasi-Newton Methods
In this article, we consider the correction of metric matrices in quasi-Newton methods (QNM) from the perspective of machine learning theory. Based on training information for estimating the matrix of the second derivatives of a function, we formulate a ...
Vladimir Krutikov +4 more
doaj +1 more source
A global optimization approach for the linear two-level program
Linear two-level programming deals with optimization problems in which the constraint region is implicity determined by another optimization problem. Mathematical programs of this type arise in connection with policy problems to which the Stackelberg ...
Tuy, Hoang, +2 more
core +1 more source
ABSTRACT Relapsed and/or refractory (R/R) pediatric acute leukemia carries a dismal prognosis, largely driven by chemoresistance to conventional salvage therapy. The BH3‐mimetic venetoclax, combined with chemotherapy or hypomethylating agents, has demonstrated efficacy in small clinical trials.
Katherine S. Colman +9 more
wiley +1 more source
Continuous GRASP with a local active-set method for bound-constrained global optimization
Global optimization, Stochastic methods, Active-set methods, Heuristic, CGRASP, GENCAN,
GOZZI, Erico M. +3 more
core +1 more source
ABSTRACT Febrile neutropenia (FN) is a frequent and serious complication in children receiving cancer therapy. Standardizing FN management across Asia is challenging due to variable healthcare infrastructure, diagnostic capacity, and infection patterns; however, it could improve resource use and patient outcomes.
Joliza Patricia Cañeba +29 more
wiley +1 more source
A Procedure of Global Optimization and its Application to Estimate Parameters in Interaction Spatial Models [PDF]
This work concerns the calibration of trip distribution models issued from Transportation Planning. The optimal estimators are the global minima of a non-convex function.
Bez Edson Tadeu +2 more
doaj +1 more source
Subdomain separability in global optimization
AbstractWe introduce a generalization of separability for global optimization, presented in the context of a simple branch and bound method. Our results apply to continuously differentiable objective functions implemented as computer programs. A significant search space reduction can be expected to yield an acceleration of any global optimization ...
Jens Deussen, Uwe Naumann
openaire +5 more sources
ABSTRACT Background Outcomes in relapsed or refractory pediatric and AYA bone sarcomas remain poor, and the impact of early referral to specialized sarcoma centers on survival is unclear. Early centralization of care may improve local and systemic treatment quality, but evidence in this population is limited.
Justyna Antoniuk‐Majchrzak +9 more
wiley +1 more source
This article considers a box-constrained global optimization problem for Lipschitz continuous functions with an unknown Lipschitz constant. The well-known derivative-free global search algorithm DIRECT (DIvide RECTangle) is a promising approach for such ...
Linas Stripinis, Remigijus Paulavičius
doaj +1 more source
Novelty search for global optimization
Novelty search is a tool in evolutionary and swarm robotics for maintaining the diversity of population needed for continuous robotic operation. It enables nature-inspired algorithms to evaluate solutions on the basis of the distance to their k-nearest neighbors in the search space.
Iztok Fister 0001 +7 more
openaire +5 more sources

