Results 11 to 20 of about 241,820 (264)
Noncomputable Conditional Distributions [PDF]
2011 IEEE 26th Annual Symposium on Logic in Computer Science, 2011 We study the computability of conditional probability, a fundamental notion in probability theory and Bayesian statistics. In the elementary discrete setting, a ratio of probabilities defines conditional probability. In more general settings, conditional probability is defined axiomatically, and the search for more constructive definitions is the ...
Nathanael L. Ackerman +2 more
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Composition Algorithms for Conditional Distributions
, 2022 This chapter is about two recently published algorithms that can be used to sample from conditional distributions. We show how the efficiency of the algorithms can be improved when a sample is required from many conditional distributions. Using real-data examples from educational measurement, we show how the algorithms can be used to sample from ...
Maarten Marsman +2 more
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MOMENTS OF THE LENGTH OF LINE SEGMENTS IN HOMOGENEOUS PLANAR STIT TESSELLATIONS
Image Analysis and Stereology, 2011 Homogeneous planar tessellations stable under iteration (STIT tessellations) are considered. Using recent results about the joint distribution of direction and length of the typical I-, K- and J-segment we prove closed formulas for the first, second and ...
Christoph Thäle
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Risks, 2021 A comprehensive auto insurance policy usually provides the broadest protection for the most common events for which the policyholder would file a claim.
Emilio Gómez-Déniz +1 more
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Optimality conditions for distributive justice [PDF]
International Transactions in Operational Research, 2010 AbstractThis paper uses optimization theory to address a fundamental question of ethics: how to divide resources justly among individuals, groups, or organizations. It formulates utilitarian and Rawlsian criteria for distributive justice as optimization problems.
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Arbitrary Conditional Distributions with Energy
CoRR, 2021 Modeling distributions of covariates, or density estimation, is a core challenge in unsupervised learning. However, the majority of work only considers the joint distribution, which has limited utility in practical situations. A more general and useful problem is arbitrary conditional density estimation, which aims to model any possible conditional ...
Ryan R. Strauss, Junier B. Oliva
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Economic Journal of Emerging Markets, 2011 This paper uncovers the nature of conditional correlations between and volatility spillovers across bond, stock and foreign exchange in Indonesia, Malaysia, the Philippines, and Thailand.
Abdul Hakim
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Machine Learning: Science and Technology, 2023 Learning over the domain of 3D graphs has applications in a number of scientific and engineering disciplines, including molecular chemistry, high energy physics, and computer vision.
Eyal Rozenberg, Daniel Freedman
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Zhongguo dianliAccurately accounting for the errors in meteorological parameter predictions is essential for the precise forecasting of dynamic current-carrying capacity in overhead power transmission lines.
Hanru LI +6 more
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IEEE Access, 2018 Ordering decision-making on spare parts is crucial in maximizing aircraft utilization and minimizing operating costs. This paper develops an approach of ordering decision-making for civil aircraft spare parts based on a one-sample prediction. Engineering
Yongquan Sun +3 more
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