Results 51 to 60 of about 25,488 (167)
International Journal of STEM EducationBackground STEM participation is at record highs, yet scientific knowledge often fails to translate into effective responses to urgent social and environmental challenges, resulting in a growing knowledge–action gap. This study examines how early college
Christopher Irwin +4 more
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MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model
Applied Sciences, 2019 Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BNs) with First-Order Logic (FOL). MEBN has sufficient expressive power for general-purpose knowledge representation and reasoning, and is the ...
Cheol Young Park +1 more
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Change of Representation for Statistical Relational Learning. [PDF]
, 2007 Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learning for SRL, in which the view of a relational database can be automatically modified, yielding more accurate statistical models.
Davis, Jesse +5 more
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A Systematic Evaluation Method of Graph-Derived Signals for Tabular Machine Learning
Applied SciencesWhile graph-derived signals are widely used in tabular learning, existing studies typically rely on limited experimental setups and average performance comparisons, leaving the statistical reliability and robustness of observed gains largely unexplored ...
Mario Heidrich +3 more
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Limitations of Statistical Learning: the Case of Paradigmatic Relations. [PDF]
, 2020 Extensive statistical learning literature suggests that regularities between co-occurring items can be learned implicitly.However, little is known whether higher-order statistics, such as paradigmatic relations, can be learned implicitly. Paradig-matic relations link items that may not co-occur but share each others patterns of co-occurrence.
Yim, Hyungwook +4 more
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The effect of lexicalization biases on cross-situational statistical learning of novel verbs
Language and CognitionLanguages vary in the mapping of relational terms onto events. For instance, English motion descriptions favor manner (how something moves) verbs over path (where something move) verbs, whereas those of other languages, like Spanish, show the opposite ...
Nathan R. George +3 more
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Directed models for statistical relational learning [PDF]
, 2012 Statistical Relational Learning is a new branch of machine learning that aims to model a joint distribution over relational data. Relational data consists of different types of objects where each object is characterized with a different set of attributes.
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Towards Multistrategic Statistical Relational Learning [PDF]
, 2010 Statistical Relational Learning (SRL) is a growing field in Machine Learning that aims at the integration of logic-based learning approaches with probabilistic graphical models. Markov Logic Networks (MLNs) are one of the state-of-the-art SRL models that combine first-order logic and Markov networks (MNs) by attaching weights to first-order formulas ...
BIBA M. +2 more
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SAGE OpenThis article examines the relationship between dialogic STEAM education (Science, Technology, Engineering, Arts, and Mathematics) and the development of critical thinking among high school students in Northeastern Mexico during the COVID-19 pandemic. The
Juan Manuel Fernández-Cárdenas +1 more
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Statistical Relational Learning to Recognise Textual Entailment
, 2014 We propose a novel approach to recognise textual entailment RTE following a two-stage architecture --- alignment and decision --- where both stages are based on semantic representations. In the alignment stage the entailment candidate pairs are represented and aligned using predicate-argument structures.
Miguel Rios 0001 +3 more
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