Results 81 to 90 of about 95,488 (287)
A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching
, 2017 We study the quadratic assignment problem, in computer vision also known as graph matching. Two leading solvers for this problem optimize the Lagrange decomposition duals with sub-gradient and dual ascent (also known as message passing) updates.
Alhaija, Hassan Abu +4 more
core +1 more source
Advanced Intelligent Systems, EarlyView.Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty +2 more
wiley +1 more source
Solving the quadratic assignment problem by neural networks [PDF]
, 2013 The Quadratic Assignment Problem (QAP) was introduced by Koopmans and Beckmann in 1957 as a mathematical model for the location of a set of indivisible economical activities.
Domínguez, Enrique
core
Advanced Intelligent Systems, EarlyView.This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
A hybrid algorithm combining lexisearch and genetic algorithms for the quadratic assignment problem
Cogent Engineering, 2018 Lexisearch and genetic algorithms are two different types of methods for solving combinatorial optimization problems. Lexisearch algorithm gives us exact optimal solution, whereas, genetic algorithms give heuristic solution to a problem. In this paper, a
Zakir Hussain Ahmed
doaj +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
Advanced Intelligent Systems, EarlyView.This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Development of configurations for lookup table–based Embryonics using graphic mapping: A case study
Advances in Mechanical Engineering, 2015 This article presents the development of configurations for bio-inspired self-healing cellular arrays known as Embryonics (embryonic electronics). In the Embryonics design, the configurations are employed to define the functionality and connections of ...
Qingqi Zhuo +3 more
doaj +1 more source
Metaheuristic algorithms for the quadratic assignment problem
2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS), 2013 This paper presents two meta-heuristic algorithms to solve the quadratic assignment problem. The iterated greedy algorithm has two main components, which are destruction and construction procedures. The algorithm starts from an initial solution and then iterates through a main loop, where first a partial candidate solution is obtained by removing a ...
Tasgetiren, M.F. +3 more
openaire +3 more sources
SciLitMiner: An Intelligent System for Scientific Literature Mining and Knowledge Discovery
Advanced Intelligent Systems, EarlyView.SciLitMiner is an intelligent system that federately ingests scientific literature, filters it using advanced information retrieval methods, and applies retrieval‐augmented generation tailored to scientific domains. Demonstrated on creep deformation in γ‐TiAl alloys, SciLitMiner provides a controlled workflow for systematic knowledge discovery and ...
Vipul Gupta +3 more
wiley +1 more source