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Frontiers in Psychology, 2023 IntroductionWith the continuous expansion of higher education worldwide, the academic performance of first-generation college students has become an essential topic in the scope of international educational research.
Xiaojing Li, Weitong Liu, Ke Hu
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Wavelet-Based Classification of Enhanced Melanoma Skin Lesions through Deep Neural Architectures
Information, 2022 In recent years, skin cancer diagnosis has been aided by the most sophisticated and advanced machine learning algorithms, primarily implemented in the spatial domain.
Premaladha Jayaraman +6 more
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Developmental Cognitive Neuroscience, 2023 Using event-related potentials (ERPs), this study investigated how the brains of Chinese children of different ages extract and encode relational patterns contained in orthographic input. Ninety-nine Chinese children in Grades 1-3 performed an artificial
Shelley Xiuli Tong +4 more
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Function-Based Search of Place Using Theoretical, Empirical and Probabilistic Patterns
ISPRS International Journal of Geo-Information, 2019 Searching for places rather than traditional keyword-based search represents significant challenges. The most prevalent method of addressing place-related queries is based on place names but has limited potential due to the vagueness of natural language ...
Emmanuel Papadakis +3 more
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Statistical Relational Learning [PDF]
, 2013 Relational learning refers to learning from data that have a complex structure. This structure may be either internal (a data instance may itself have a complex structure) or external (relationships between this instance and other data elements). Statistical relational learning refers to the use of statistical learning methods in a relational learning ...
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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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Human-Guided Learning for Probabilistic Logic Models
Frontiers in Robotics and AI, 2018 Advice-giving has been long explored in the artificial intelligence community to build robust learning algorithms when the data is noisy, incorrect or even insufficient. While logic based systems were effectively used in building expert systems, the role
Phillip Odom, Sriraam Natarajan
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Connection Science, 2020 Similarity-based generalisation is fundamental to human cognition, and the ability to draw analogies based on relational similarities between superficially different domains is crucial for reasoning and inference.
Paul H. Thibodeau +2 more
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Why deterministic logic is hard to learn but Statistical Relational Learning works [PDF]
, 2010 A brief note on why we think that the statistical relational learning framework is a great advancement over deterministic logic -- in particular in the context of model-based Reinforcement ...
Toussaint, Marc
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A social work study on the impact of age, gender and residential status on drug addiction [PDF]
Management Science Letters, 2013 During the past few years, there have been growing interests on intellectual capital due to industrial changes on the market. Thus, identifying different ways to create, manage, and evaluate the impact of intellectual capital has remained an open area of
Mohammad Reza Iravani +4 more
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