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Learning Sparse Sentence Encoding without Supervision: An Exploration of Sparsity in Variational Autoencoders
[article]
2021
arXiv
pre-print
It has been long known that sparsity is an effective inductive bias for learning efficient representation of data in vectors with fixed dimensionality, and it has been explored in many areas of representation learning. Of particular interest to this work is the investigation of the sparsity within the VAE framework which has been explored a lot in the image domain, but has been lacking even a basic level of exploration in NLP. Additionally, NLP is also lagging behind in terms of learning sparse
arXiv:2009.12421v2
fatcat:4ym6vjyfnnb7vop322nfrn4ogu