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Physiological parameters and learning
30th Annual Frontiers in Education Conference. Building on A Century of Progress in Engineering Education. Conference Proceedings (IEEE Cat. No.00CH37135), 2002Whilst much attention is paid to the quality and the avenues of presentation of educational material, there seems to be little consideration given to human physiological processes of information ingestion and assimilation when planning the educational experience.
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Bayesian Learning and Evolutionary Parameter Optimization
2001Summary: I want to argue that the combination of evolutionary algorithms and neural networks can be fruitful in several ways. When estimating a functional relationship on the basis of empirical data we face three basic problems. Firstly, we have to deal with noisy and finite-sized data sets which is usually done be regularization techniques, for ...
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Age and Sex Parameters in Psychomotor Learning
Perceptual and Motor Skills, 1964Quantitative relationships were sought among psychomotor response speed (R), number of practice trials (T), chronological age (A), and biological sex (S) for 600 S s in 30 groups between the ages of 8 and 87 yr.
C, NOBLE, B L, BAKER, T A, JONES
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Parameter and Structure Learning Algorithms for Statistical Relational Learning. [PDF]
, 2012 My research activity focuses on the field of Machine Learning. Two key challenges in most machine learning applications are uncertainty and complexity. The standard framework for handling uncertainty is probability, for complexity is first-order logic. Thus we would like to be able to learn and perform inference in representation languages that combine
BELLODI, Elena, RIGUZZI, Fabrizio
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Learning the Parameters of Probabilistic Description Logics. [PDF]
, 2014 Uncertain information is ubiquitous in the Semantic Web, due to methods used for collecting data and to the inherently distributed nature of the data sources. It is thus very important to develop proba- bilistic Description Logics (DLs) so that the uncertainty is directly rep- resented and managed at the language level.
RIGUZZI, Fabrizio +3 more
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Machine learning for microbiologists
Nature Reviews Microbiology, 2023Francesco Asnicar +2 more
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Machine learning methods to model multicellular complexity and tissue specificity
Nature Reviews Materials, 2021Rachel S G Sealfon +2 more
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Machine learning sheds light on microbial dark proteins
Nature Reviews Microbiology, 2023A T Hammack +2 more
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