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• Topic models take a corpus of documents as input, and jointly cluster: words by the documents that they occur in, and documents by the words that they contain • If the corpus is small and/or the documents are short, these clusters will be noisy • Latent feature representations of words learnt from large external corpora (e.g., word2vec, Glove) capture(More)
Many parsers learn sparse class distributions over trees to model natural language. Recursive Neural Networks (RNN) use much denser representations, yet can still achieve an F-score of 92.06% for right binarized sentences up to 15 words long. We examine an RNN model by comparing it with an abstract generative probabilistic model using a Deep Belief Network(More)
George Washington University's Himmelfarb Health Sciences Library was investigating adding PDA resources to the collection when a medical education grant was received. Funds were used for a pilot project to compare PDA use by third-year medical students (MSIII), fourth-year medical students (MSIV), second-year physician assistant (PAII) students, and(More)
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