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Two SVDs produce more focal deep learning representations
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 adaptation and other desirable functionalities.
Cutting Recursive Autoencoder Trees
This makes the analysis of learned structures particularly difficult.
Bootstrapping Sentiment Labels For Unannotated Documents With Polarity PageRank
We present a novel graph-theoretic method for the initial annotation of high-confidence training data for bootstrapping sentiment classifiers.
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