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• W3098205501 abstract "We propose a modified expectation-maximization algorithm by introducing the concept of quantum annealing, which we call the deterministic quantum annealing expectation-maximization (DQAEM) algorithm. The expectation-maximization (EM) algorithm is an established algorithm to compute maximum likelihood estimates and applied to many practical applications. However, it is known that EM heavily depends on initial values and its estimates are sometimes trapped by local optima. To solve such a problem, quantum annealing (QA) was proposed as a novel optimization approach motivated by quantum mechanics. By employing QA, we then formulate DQAEM and present a theorem that supports its stability. Finally, we demonstrate numerical simulations to confirm its efficiency." @default.
• W3098205501 created "2020-11-23" @default.
• W3098205501 creator A5029092749 @default.
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• W3098205501 date "2016-12-01" @default.
• W3098205501 modified "2023-10-01" @default.
• W3098205501 title "Relaxation of the EM algorithm via quantum annealing for Gaussian mixture models" @default.
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• W3098205501 doi "https://doi.org/10.1109/cdc.2016.7798981" @default.
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