klotz: neural network* + nlp*

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  1. However it is interesting that LSTM can achieve good performance
    with word vectors based on a small corpus even though it scored terrible in the semantic and syntactic analysis.

    LSTM does perform better than the other classifiers, but it does require more data. If NLP tasks are to be solved in other domains that do not generate enough data for a LSTM to work properly it would be advisable to train a SVM using AvgWV. LSTM is more adaptable but knowing how to optimise the network does require domain knowledge and experience with gradient-decent classifiers.
  2. 2018-07-18 Tags: , , , by klotz
  3. 2018-07-18 Tags: , , , , , , by klotz
  4. 2018-06-22 Tags: , , , , , by klotz
  5. Semi-Supervised Learning with Multi-View Embedding:
    Rie Johnson
    RJ Research Consulting
    Tarrytown, NY, USA
    Tong Zhang
    Baidu Inc., Beijing, China
    Rutgers University, Piscataway, NJ, USA
    2015-09-09 Tags: , , , by klotz

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