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Found 3 papers, 2 papers with code
Compressing Latent Space via Least Volume
This paper introduces Least Volume-a simple yet effective regularization inspired by geometric intuition-that can reduce the necessary number of latent dimensions needed by an autoencoder without requiring any prior knowledge of the intrinsic dimensionality of the dataset.
Document Set Expansion with Positive-Unlabelled Learning Using Intractable Density Estimation
The Document Set Expansion (DSE) task involves identifying relevant documents from large collections based on a limited set of example documents.
Document Set Expansion with Positive-Unlabeled Learning: A Density Estimation-based Approach
Previous work shows that PU learning is a promising method for this task.
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