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In short, the fellowship is exploring the creation of reduced-dimensional term-topic matrices for the HathiTrust collection. This includes the exploration of scalable methods for dimension reduction/topic modeling (LSA/pLSA, LDA, autoencoders) for the full collection.
Updates
12/6/2017
- BW allocation approved, still waiting for access.
- Will work with Capitanu on sync'ing initial data for evaluation of deeplearning4j by end of week.
- Will meet with Co-PI Bhattacharyya 12/11 about BW project we are piggy-backing on
11/27/2017
- Conference call (Willis, Capitanu)
- Still waiting for BW allocation
- Boris explored deploying TensorFlow on TORQUE cluster and concluded that it's too complicated given that the deeplearning4j Spark already has a variational autoencoder implementation
- Will focus on deeplearning4j for now. Craig to request update on BW access.
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