Neural nonnegative matrix factorization for hierarchical multilayer topic modeling

Neural nonnegative matrix factorization for hierarchical multilayer topic modeling

We introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data. Datasets with hierarchical structure arise in a wide variety of fields, such as document classification, image processing, and bioinformatics. Neural NMF recursively...

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Bibliographic Details
Main Authors: Haddock, Jamie, Will, Tyler, Vendrow, Joshua, Zhang, Runyu, Molitor, Denali, Needell, Deanna, Gao, Mengdi, Sadovnik, Eli
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Springer International Publishing 2024
Online Access:https://hdl.handle.net/1721.1/153309

Internet

https://hdl.handle.net/1721.1/153309

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