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Liftability of probabilistic inference: Upper and lower bounds
, 2012 We introduce a general framework for defining classes of probabilistic-logic models and associated classes of inference problems. Within this framework we investigate the complexity of inference in terms of the size of logical variable domains, query and evidence, corresponding to different notions of liftability. Surveying existing and introducing new
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Tight Bounds for Joint Distribution Functions of Order Statistics Under <i>k</i>-Independence. [PDF]
Entropy (Basel)Okolewski A, Blazejczyk-Okolewska B.
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Investigations of sharp bounds for causal effects under selection bias. [PDF]
Stat Methods Med ResZetterstrom S +2 more
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Radar-based inspiratory-to-expiratory time ratio estimation: a validation study. [PDF]
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Geometry-Based Bounds on the Capacity of Peak-Limited and Band-Limited Signals over the Additive White Gaussian Noise Channel at a High SNR. [PDF]
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UMLoc: Uncertainty-Aware Map-Constrained Inertial Localization with Quantified Bounds. [PDF]
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The Upper and Lower Bounds of the Prediction Accuracies of Ensemble Methods for Binary Classification. [PDF]
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Counting Subnetworks Under Gene Duplication in Genetic Regulatory Networks. [PDF]
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