Results 31 to 40 of about 561,186 (166)
Learning high-order interactions for polygenic risk prediction.
PLoS ONE, 2023 Within the framework of precision medicine, the stratification of individual genetic susceptibility based on inherited DNA variation has paramount relevance. However, one of the most relevant pitfalls of traditional Polygenic Risk Scores (PRS) approaches
Michela C Massi +9 more
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Learning in Repeated Interactions on Networks
Proceedings of the 23rd ACM Conference on Economics and Computation, 2022 We study how long‐lived, rational agents learn in a social network. In every period, after observing the past actions of his neighbors, each agent receives a private signal, and chooses an action whose payoff depends only on the state. Since equilibrium actions depend on higher‐order beliefs, it is difficult to characterize behavior.
Huang, Wanying +2 more
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Bayesian Social Learning with Local Interactions
Games, 2010 We study social learning in a large population of agents who only observe the actions taken by their neighbours. Agents have to choose one, out of two, reversible actions, each optimal in one, out of two, unknown states of the world.
Antonella Ianni, Antonio Guarino
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Sensorimotor Interactions in Speech Learning
i-Perception, 2011 Auditory input is essential for normal speech development and plays a key role in speech production throughout the life span. In traditional models, auditory input plays two critical roles: 1) establishing the acoustic correlates of speech sounds that ...
Douglas M Shiller
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Towards Learning by Interacting
, 2009 Legacy description not ...
Wrede, Britta +8 more
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Interactive Learning of Pattern Rankings [PDF]
International Journal on Artificial Intelligence Tools, 2014 Pattern mining provides useful tools for exploratory data analysis. Numerous efficient algorithms exist that are able to discover various types of patterns in large datasets. Unfortunately, the problem of identifying patterns that are genuinely interesting to a particular user remains challenging. Current approaches generally require considerable data
Vladimir Dzyuba +3 more
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Screening drug-target interactions with positive-unlabeled learning
Scientific Reports, 2017 Identifying drug-target interaction (DTI) candidates is crucial for drug repositioning. However, usually only positive DTIs are deposited in known databases, which challenges computational methods to predict novel DTIs due to the lack of negative samples.
Lihong Peng +6 more
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Learning epistatic gene interactions from perturbation screens.
PLoS ONE, 2021 The treatment of complex diseases often relies on combinatorial therapy, a strategy where drugs are used to target multiple genes simultaneously. Promising candidate genes for combinatorial perturbation often constitute epistatic genes, i.e., genes which
Kieran Elmes +5 more
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The Asia Pacific Scholar, 2021 Introduction: A novel initiative allowed third year medical students to pursue experiential learning during a year-long Enrichment Year programme as part of the core curriculum.
Pauline Luk, Julie Chen
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NeuroImage, 2022 Corticocortical neuroplastic changes from higher-order cortices to primary motor cortex (M1) have been described for procedural sequence learning. The dorsolateral prefrontal cortex (DLPFC) plays critical roles in cognition, including in motor learning ...
Na Cao +6 more
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