An improved differential evolution algorithm for learning high-fidelity quantum controls
Sign Up to like & getrecommendations! Published in 2019 at "Science Bulletin"
DOI: 10.1016/j.scib.2019.07.013
Abstract: Abstract Precisely and efficiently designing control pulses for the preparation of quantum states and quantum gates are the fundamental tasks for quantum computation. Gradient-based optimal control methods are the routine to design such pulses. However,… read more here.
Keywords: evolution algorithm; algorithm learning; improved differential; differential evolution ... See more keywords
Distributed Algorithm for Learning to Coordinate in Infrastructure-Less Network
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2018.2890226
Abstract: We consider the spectrum access in an unlicensed spectrum (i.e., no incumbent users) for infrastructure-less networks where the number of users are unknown and they cannot coordinate with others due to lack of a control… read more here.
Keywords: distributed algorithm; algorithm learning; network; infrastructure less ... See more keywords
Deep Semi-Supervised Algorithm for Learning Cluster-Oriented Representations of Medical Images Using Partially Observable DICOM Tags and Images
Sign Up to like & getrecommendations! Published in 2021 at "Diagnostics"
DOI: 10.3390/diagnostics11101920
Abstract: The task of automatically extracting large homogeneous datasets of medical images based on detailed criteria and/or semantic similarity can be challenging because the acquisition and storage of medical images in clinical practice is not fully… read more here.
Keywords: cluster oriented; dicom tags; medical images; learning cluster ... See more keywords
Polynomial-Time Algorithm for Learning Optimal BFS-Consistent Dynamic Bayesian Networks
Sign Up to like & getrecommendations! Published in 2018 at "Entropy"
DOI: 10.3390/e20040274
Abstract: Dynamic Bayesian networks (DBN) are powerful probabilistic representations that model stochastic processes. They consist of a prior network, representing the distribution over the initial variables, and a set of transition networks, representing the transition distribution… read more here.
Keywords: polynomial time; dynamic bayesian; bayesian networks; time ... See more keywords
A Dual-Population Genetic Algorithm with Q-Learning for Multi-Objective Distributed Hybrid Flow Shop Scheduling Problem
Sign Up to like & getrecommendations! Published in 2023 at "Symmetry"
DOI: 10.3390/sym15040836
Abstract: In real-world production processes, the same enterprise often has multiple factories or one factory has multiple production lines, and multiple objectives need to be considered in the production process. A dual-population genetic algorithm with Q-learning… read more here.
Keywords: population genetic; distributed hybrid; algorithm learning; genetic algorithm ... See more keywords