Results 41 to 50 of about 7,641,552 (201)

Weakly Convex Ridge Regularization for 3D Non‐Cartesian MRI Reconstruction

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose While highly accelerated non‐Cartesian acquisition protocols significantly reduce scan time, they often entail long reconstruction delays for 3D data. Deep learning–based reconstruction methods can alleviate this, but typically rely on complex, highly parametrized architectures.
German Shâma Wache, Chaithya G R, Asma Tanabene, Sebastian Neumayer   +3 more
wiley   +1 more source

Semidefinite relaxation based branch-and-bound method for nonconvex quadratic programming [PDF]

, 2006
Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2006.Includes bibliographical references (leaves 73-75).In this thesis, we use a semidefinite relaxation based branch-and-bound method to solve ...
Hu, Sha, S.M. Massachusetts Institute of Technology
core  

Safeguarded Reinforcement Learning for Dynamic Environments

Optimal Control Applications and Methods, EarlyView.
This paper uses a combination of Reinforcement Learning and Funnel Control to train a fast and safe controller for systems operating in changing environments. Furthermore, the presented formulation overcomes former limitations associated with the need for predefined reference trajectories.
Simon Gottschalk
wiley   +1 more source

Enhancing Drone Light Shows Performances: Optimal Allocation and Trajectories for Swarm Drone Formations

Journal of Field Robotics, EarlyView.
ABSTRACT Drone light shows (DLShows) represent a rapidly growing application of swarm robotics, creating captivating aerial displays through the synchronized flight of hundreds or thousands of unmanned aerial vehicles (UAVs) as environmentally friendly and reusable alternatives to traditional pyrotechnics.
Yunes Alqudsi
wiley   +1 more source

Routing and Downlink Resource Allocation for Multicast Traffic in LEO Satellite Constellations

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT In this work, we optimize unicast and multicast traffic delivery over non‐terrestrial networks (NTNs) to users on the ground through direct satellite downlink (DL). We consider a gateway‐free mesh architecture with low Earth orbit (LEO) satellites interconnected via inter‐satellite links (ISLs), where unicast and multicast services compete for
Federico Lozano‐Cuadra, Israel Leyva‐Mayorga, Jimmy Jessen Nielsen, Beatriz Soret   +3 more
wiley   +1 more source

ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations

, 2014
This manuscript introduces ANTIGONE, Algorithms for coNTinuous/Integer Global Optimization of Nonlinear Equations, a general mixed-integer nonlinear global optimization framework. ANTIGONE is the evolution of the Global Mixed-Integer Quadratic Optimizer,
Floudas, Christodoulos A, Misener, Ruth
core   +1 more source

Bounding-focused discretization methods for the global optimization of nonconvex semi-infinite programs

Computational Optimization and Applications
We use sensitivity analysis to design bounding-focused discretization (cutting-surface) methods for the global optimization of nonconvex semi-infinite programs (SIPs). We begin by formulating the optimal bounding-focused discretization of SIPs as a max-min problem and propose variants that are more computationally tractable.
Evren Mert Turan, Johannes Jäschke, Rohit Kannan   +2 more
openaire   +4 more sources

Double‐Integration‐Enhanced Stochastic Gradient Descent Based on Neural Dynamics for Improving Generalisation

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, Longbang Wang, Jiexing Li, Jicheng Li   +3 more
wiley   +1 more source

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

BMC Bioinformatics, 2009
Background Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering.
Sorribas Albert, Guillén-Gosálbez Gonzalo   +1 more
doaj   +1 more source

Research on Embodied Intelligence Technology for Electric Power Equipment Based on Large‐Scale Pre‐Trained Models

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, Rui Song, Ankai Zhang, Wenhao Mo, Wenjin Ji   +4 more
wiley   +1 more source