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Modeling EEG Spectral Features through Warped Functional Mixed Membership Models
Emma Landry, Damla Senturk, Shafali Jeste +3
A common concern in the field of functional data analysis is the challenge of temporal misalignment, which is typically addressed using curve registration methods. Currently, most…
Covariate Adjusted Functional Mixed Membership Models
Nicholas Marco, Damla Şentürk, Shafali Jeste +3
Mixed membership models are a flexible class of probabilistic data representations used for unsupervised and semi-supervised learning, allowing each observation to partially belong…
Flexible Regularized Estimation in High-Dimensional Mixed Membership Models
Nicholas Marco, Damla Şentürk, Shafali Jeste +3
Mixed membership models are an extension of finite mixture models, where each observation can partially belong to more than one mixture component. A probabilistic framework for mix…
Functional Mixed Membership Models
Nicholas Marco, Damla Şentürk, Shafali Jeste +3
Mixed membership models, or partial membership models, are a flexible unsupervised learning method that allows each observation to belong to multiple clusters. In this paper, we pr…