Results 61 to 70 of about 1,895,431 (338)
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1953 Summary The subject matter of mathematical statistics may be divided into two parts, the theory of probability and the theory of inference. The first is concerned with deductions from the population to the sample; the second with inferences from the sample to the population, and may further be subdivided into the design and analysis of ...
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Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Wiggles and Curves: The Analysis of Ordinal Patterns
Problemy Zarządzania, 2016 Almost all social science data are analysed with variants of the General Linear Model (GLM): regression analyses, analyses of variance, factor analyses, path analyses and the like.
Warren Thorngate, Chunyun Ma
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Molecular Oncology, EarlyView.Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
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Frontiers in NeuroscienceUnderstanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning ...
Alexandre Bittar +2 more
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Performance of Some Estimators of Relative Variability
Frontiers in Applied Mathematics and Statistics, 2019 The classic coefficient of variation (CV) is the ratio of the standard deviation to the mean and can be used to compare normally distributed data with respect to their variability, this measure has been widely used in many fields. In the Social Sciences,
Raydonal Ospina +1 more
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Lifted Variable Elimination: Decoupling the Operators from the Constraint Language [PDF]
Journal Of Artificial Intelligence Research, Volume 47, pages
393-439, 2013, 2014 Lifted probabilistic inference algorithms exploit regularities in the structure of graphical models to perform inference more efficiently. More specifically, they identify groups of interchangeable variables and perform inference once per group, as opposed to once per variable.
arxiv +1 more source
Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results [PDF]
, 2014 The classical setting of community detection consists of networks exhibiting a clustered structure. To more accurately model real systems we consider a class of networks (i) whose edges may carry labels and (ii) which may lack a clustered structure ...
Edge Label +7 more
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Combination Strategies for Semantic Role Labeling
, 2011 This paper introduces and analyzes a battery of inference models for the problem of semantic role labeling: one based on constraint satisfaction, and several strategies that model the inference as a meta-learning problem using discriminative classifiers.
Carreras, X. +3 more
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Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer
Molecular Oncology, EarlyView.We used whole exome and RNA‐sequencing to profile divergent genomic and transcriptomic landscapes of microsatellite stable (MSS) and microsatellite instable (MSI) colorectal cancer. Alterations were classified using a computational score for integrative cancer variant annotation and prioritization.
Efstathios‐Iason Vlachavas +15 more
wiley +1 more source