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Low-Latency Realism Through Randomized Distributed Function Computations: A Shannon Theoretic Approach. [PDF]
Günlü O, Skorski M, Poor HV.
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Probing Phase Transitions of Finite Directed Polymers near a Corrugated Wall via Two-Replica Analysis. [PDF]
Xu R, Nechaev S.
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A benchmarking study of feature screening approaches across type 1 diabetes omics studies classification settings. [PDF]
VonKaenel ED +5 more
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A dependent and censored first hitting-time model with compound Poisson processes. [PDF]
Escobar-Bach M, Popier A, Sahin M.
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Scale-dependent universality class crossover in magnetic skyrmion polymers. [PDF]
Silva RL, Silva RC, Stamps RL.
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Asymptotic minimax testing of independence hypothesis
Journal of Soviet Mathematics, 1989See the review in Zbl 0649.62038.
Yu I Ingster
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Asymptotic independence of median and MAD
Statistics and Probability Letters, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On asymptotic independence of order statistics
Annals of the Institute of Statistical Mathematics, 1970Sadao Ikeda
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Asymptotic Independence and Additive Functionals
Journal of Theoretical Probability, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Csáki, Endre, Földes, Antónia
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Asymptotically Independent Samplers
2018Markov Chain Monte Carlo (MCMC) methods are possibly the most popular tools for random sampling nowadays. They generate “chains” (sequences) of samples from a target distribution that can be selected with few constraints. However, as highlighted by the term “chain,” the draws output by the MCMC method are statistically dependent (and often highly ...
Luca Martino +2 more
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