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Learning of couplings for random asymmetric kinetic Ising models revisited: random correlation matrices and learning curves
Citation key Ba-RoOp15
Author Ludovica Bachschmid-Romano and Manfred Opper
Pages P09016
Year 2015
DOI 10.1088} ISSN =1742-5468 url={http://stacks.iop.org/1742-5468/2015/i=9/a=P09016
Journal Journal of Statistical Mechanics: Theory and Experiment
Volume 2015
Number 9
Publisher IOP Publishing
Abstract We study analytically the performance of a recently proposed algorithm for learning the couplings of a random asymmetric kinetic Ising model from finite length trajectories of the spin dynamics. Our analysis shows the importance of the nontrivial equal time correlations between spins induced by the dynamics for the speed of learning. These correlations become more important as the spin’s stochasticity is decreased. We also analyse the deviation of the estimation error
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