Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 7 of 7 for “"unsupervised modeling"”.
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Unsupervised modeling of latent topics and lexical units in speech audio
… of a collection of speech data in a completely unsupervised fashion without the benefit of any transcriptions or annotations of the data. In this thesis, we describe a zero-resource framework that automatically discovers important words, phrases and topical themes present in an audio corpus. …
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Unsupervised learning of morphological forests
This thesis focuses on unsupervised modeling of morphological families, collectively comprising a forest over the language vocabulary. This formulation enables us to capture edge-wise properties reflecting single-step morphological derivations, along with global distributional properties of the …
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Semantic spaces : behavior, language and word learning in the Human Speechome corpus
… representation is shown to be useful for the unsupervised modeling, clustering and exploration of the data, particularly when it is combined with text transcripts of the speech. Novel methods are introduced to perform Spatial Latent Semantic Analysis - extending the popular framework for topic …
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Analysis of Healthcare Coverage Using Data Mining Techniques
… problems and inconsistencies by employing unsupervised modeling including K-Means clustering algorithm. Our modeling is based on the dataset retrieved from Medical Expenditure Panel Survey with 98,175 records in the original dataset. After pre-processing the data, including binning, …
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Scientific deep learning for efficient modeling and uncertainty quantification in engineering systems
… various deep learning approaches for efficient modeling, metamodeling, and forward and inverse uncertainty quantification in engineering systems. In the first part of the dissertation, we introduce deep learning methods for efficient supervised, semi-supervised, and unsupervised modeling and …
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Patient Cohort Visual Analytics for Post-Treatment Care
… planning relies on computational cohort data modeling and, as a result, uses both objective and subjective evidence, namely, the clinician's interpretation of the modeling results. Consequently, cohort modeling and analysis depend on collaborations between clinicians and data modelers. …
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Unsupervised inference models for structural and functional properties of protein sequences
L'abstract è presente nell'allegato / the abstract is in the attachment