Results 21 to 30 of about 2,891,657 (252)
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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Multi-decadal streamflow projections for catchments in Brazil based on CMIP6 multi-model simulations and neural network embeddings for linear regression models [PDF]
Hydrology and Earth System SciencesA linear regression model is developed to link anomalies of streamflow to anomalies of precipitation amounts and temperature with the goal of making multi-decadal streamflow projections based on CMIP6 multi-model simulations.
M. Scheuerer +5 more
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Statistical learning and memory [PDF]
Cognition, 2020 Learners often need to identify and remember recurring units in continuous sequences, but the underlying mechanisms are debated. A particularly prominent candidate mechanism relies on distributional statistics such as Transitional Probabilities (TPs).
Ansgar D. Endress +2 more
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Active Learning with Statistical Models [PDF]
, 1995 For many types of machine learning algorithms, one can compute the statistically `optimal' way to select training data. In this paper, we review how optimal data selection techniques have been used with feedforward neural networks.
Cohn, D. A. +2 more
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Risks, 2017 The paper deals with defaultable markets, one of the main research areas of mathematical finance. It proposes a new approach to the theory of such markets using techniques from the calculus of optional stochastic processes on unusual probability spaces ...
Mohamed N. Abdelghani +1 more
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Multivariate Adaptive Regression Splines Enhance Genomic Prediction of Non-Additive Traits
AgronomyThe present work used Multivariate Adaptive Regression Splines (MARS) for genomic prediction and to study the non-additive fraction present in a trait. To this end, 12 scenarios for an F2 population were simulated by combining three levels of broad-sense
Maurício de Oliveira Celeri +6 more
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Theoretical characterization of uncertainty in high-dimensional linear classification
Machine Learning: Science and Technology, 2023 Being able to reliably assess not only the accuracy but also the uncertainty of models’ predictions is an important endeavor in modern machine learning. Even if the model generating the data and labels is known, computing the intrinsic uncertainty after ...
Lucas Clarté +3 more
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Statistical Learning Within Objects
Psychological Science, 2023 Research has recently shown that efficient selection relies on the implicit extraction of environmental regularities, known as statistical learning . Although this has been demonstrated for scenes, similar learning arguably also occurs for objects.
van Moorselaar, Dirk, Theeuwes, Jan
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Customized design of hearing aids using statistical shape learning [PDF]
, 2008 3D shape modeling is a crucial component of rapid prototyping systems that customize shapes of implants and prosthetic devices to a patient’s anatomy.
K. Zhou +6 more
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HeliyonNon-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide.
Saad Sahriar +6 more
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