Results 11 to 20 of about 10,338 (302)
Everything Is Prediction: Modern Machine Learning as Bayesian Inference [PDF]
EntropyWe argue that the core methods of modern machine learning—conformal prediction, large language models and in-context learning, and generative/diffusion models—are not rivals to Bayesian inference but implementations of it, almost always of its predictive
Nicholas G. Polson +2 more
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Inclusion of historical control data in the analysis of a current trial for zero-inflated count models [PDF]
Contemporary Clinical Trials CommunicationsHistorical control information can be used to improve the efficiency and precision of treatment-effect estimation in a current trial. However, this benefit depends on the similarity between historical and current controls as well as the methods used to ...
Akalu Banbeta Tereda +1 more
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On the complexity of exchanging [PDF]
Information Processing Letters, 2016 We analyze the computational complexity of the problem of deciding whether, for a given simple game, there exists the possibility of rearranging the participants in a set of $j$ given losing coalitions into a set of $j$ winning coalitions. We also look at the problem of turning winning coalitions into losing coalitions.
Xavier Molinero +2 more
openaire +7 more sources
The Computer Journal, 2003 Summary: The growing importance of electronic commerce and the increasing number of applications in this area has led research into studying methods of how to perform safe and secure online business transactions over the Internet. A central problen, in this context is that of fair exchange, i.e. how to exchange two electronic items in a fair manner. We
Pagnia, Henning +2 more
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Family-based multi-SNP X chromosome analysis using parental information
Frontiers in Genetics, 2016 We propose a method for association analysis of haplotypes on the X chromosome that offers both improved power and robustness to population stratification in studies of affected offspring and their parents if all three have been genotyped.
Alison S. Wise +3 more
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The de Finetti structure behind some norm-symmetric multivariate densities with exponential decay
Dependence Modeling, 2020 We derive a sufficient condition on the symmetric norm ||·|| such that the probability distribution associated with the density function f (x) ∝exp(−λ ||x||) is conditionally independent and identically distributed in the sense of de Finetti’s seminal ...
Mai Jan-Frederik
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A Central Limit Theorem for Predictive Distributions
Mathematics, 2021 Let S be a Borel subset of a Polish space and F the set of bounded Borel functions f:S→R. Let an(·)=P(Xn+1∈·∣X1,…,Xn) be the n-th predictive distribution corresponding to a sequence (Xn) of S-valued random variables.
Patrizia Berti +2 more
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The role of exchangeability in causal inference [PDF]
, 2022 Though the notion of exchangeability has been discussed in the causal inference literature under various guises, it has rarely taken its original meaning as a symmetry property of probability distributions.
Saarela, Olli +5 more
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Extensions Of The Concept Of Exchangeability And Their Applications [PDF]
, 2002 Permutation tests provide exact p-values in a wide variety of practical testing situations. But permutation tests rely on the assumption of exchangeability, that is, under the hypothesis, the joint distribution of the observations is invariant under ...
Good, Phillip I.
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Exchangeability-aware sum-product networks
, 2022 Sum-Product Networks (SPNs) are expressive probabilistic models that provide exact, tractable inference. They achieve this efficiency by making use of local independence.
Lüdtke, Stefan +5 more
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