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A unified Markov random field/marked point process image model and its application to computational materials

contributor authorZhao, Huixi
contributor authorComer, Mary L.
contributor authorDe Graef, Marc
date accessioned2020-03-12T22:51:11Z
date available2020-03-12T22:51:11Z
date issued2014
identifier other7026231.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1096819?show=full
formatgeneral
languageEnglish
publisherIEEE
titleA unified Markov random field/marked point process image model and its application to computational materials
typeConference Paper
contenttypeMetadata Only
identifier padid8237438
subject keywordsbiology computing
subject keywordsn gradient methods
subject keywordsn learning (artificial intelligence)
subject keywordsn neural nets
subject keywordsn biologically plausible actor-critic algorithm
subject keywordsn connectionist actor-critic algorithm
subject keywordsn dopaminergic signaling patterns
subject keywordsn intrinsic reward system
subject keywordsn model-free reinforcement learning
subject keywordsn neural actor-critic
subject keywordsn polecart problem
subject keywordsn policy gradients
subject keywordsn Backpropagation
subject keywordsn Biological system modeling
subject keywordsn Learning (artificial intelligence)
subject keywordsn Neurons
subject keywordsn Supervised learning
identifier doi10.1109/ICRA.2014.6907425
journal titlemage Processing (ICIP), 2014 IEEE International Conference on
filesize164198
citations0


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