895 citations · 2.1k across the 169 of their papers we have counts for
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Deep Learning Embeddings for Discontinuous Linguistic Units
Wenpeng Yin, Hinrich Schütze
Deep learning embeddings have been successfully used for many natural language processing problems. Embeddings are mostly computed for word forms although a number of recent papers…
Distributional Models and Deep Learning Embeddings: Combining the Best of Both Worlds
Irina Sergienya, Hinrich Schütze
There are two main approaches to the distributed representation of words: low-dimensional deep learning embeddings and high-dimensional distributional models, in which each dimensi…
Two SVDs produce more focal deep learning representations
Hinrich Schuetze, Christian Scheible
A key characteristic of work on deep learning and neural networks in general is that it relies on representations of the input that support generalization, robust inference, domain…
Cutting Recursive Autoencoder Trees
Christian Scheible, Hinrich Schuetze
Deep Learning models enjoy considerable success in Natural Language Processing. While deep architectures produce useful representations that lead to improvements in various tasks,…