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Young K TRUoNG
Steffen LaNge and Thomas ZeugmaNN
Kensuke TaNaka Mitsuhiro HoSHINO and Daishi Kuroiwa
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algorithm Claim class with M-finite complete data Computational Learning Theory Computed Tomography condition consider Corollary covariance function deconvoluted deconvoluted kernel defined definition denote density distribution dual monotonically dual weak-monotonic e-optimal policy EM algorithm exists finite cross property finite elasticity finite sets finite tell-tale fuzzy relation G N(C\S Gaussian process Gibbs differentiable Gibbs p-adic halting problem Hence hypothesis space IEEE Transactions image reconstruction indexed family inductive inference inferable from complete inferable from positive infinite sequence input Jantke Kyushu University language classes Lemma M-finite thickness Markov policy measurement errors Medical Imaging methods mind changes nonempty nonparametric obtain optimal output p-adic p-adic stationary process pdftt pftt photons pixel positive data Positron Emission Tomography problem proof of Theorem quadratic mean random range(C recursive languages respect to Q result sample satisfies space Q stationary processes Statistical Science stochastic strings Theorem 3.1 Transactions on Medical