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Showing 1 to 4 of 4 for “"distributional learning"”.
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Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis
… we demonstrate the advantage of the proposed distributional learning-based approaches over conventional methods for NGS data analysis. Distributional learning is a very powerful approach to gain biological insights from high quality NGS data. Successful applications of the proposed Bayesian …
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Experiencing language in the order that children do: Training on age-ordered child-directed speech facilitates semantic category learning in a recurrent neural network
… semantic category knowledge can be captured by a distributional learning algorithm operating over naturalistic, noisy child-directed speech (Huebner & Willits, 2018). In chapter 1 of this work, I discuss the algorithm behind this study, and its ability to represent hierarchically organized and …
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Modeling the mechanisms of verb bias learning
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01
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Linking verbs to syntax
Language learning requires learners to balance the productive power of language with its many constraints (e.g., Bowerman, 1988). One of these constraints is verb bias. Verb bias refers to the likelihood of a verb to appear in one of the multiple structures that the verb is allowed to appear in. …