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  2. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    Long short-term memory (LSTM) [1] is a type of recurrent neural network (RNN) aimed at mitigating the vanishing gradient problem [2] commonly encountered by traditional RNNs. Its relative insensitivity to gap length is its advantage over other RNNs, hidden Markov models , and other sequence learning methods.

  3. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  4. Time aware long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Time_aware_long_short-term...

    Time Aware LSTM (T-LSTM) is a long short-term memory (LSTM) unit capable of handling irregular time intervals in longitudinal patient records. T-LSTM was developed by researchers from Michigan State University, IBM Research, and Cornell University and was first presented in the Knowledge Discovery and Data Mining (KDD) conference. [1]

  5. Connectionist temporal classification - Wikipedia

    en.wikipedia.org/wiki/Connectionist_temporal...

    Connectionist temporal classification (CTC) is a type of neural network output and associated scoring function, for training recurrent neural networks (RNNs) such as LSTM networks to tackle sequence problems where the timing is variable.

  6. File:Long Short-Term Memory.svg - Wikipedia

    en.wikipedia.org/wiki/File:Long_Short-Term...

    English: A diagram for a one-unit Long Short-Term Memory (LSTM). From bottom to top : input state, hidden state and cell state, output state. Gates are sigmoïds or hyperbolic tangents. Other operators : element-wise plus and multiplication. Weights are not displayed. Inspired from Understanding LSTM, Blog of C. Olah

  7. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    A 380M-parameter model for machine translation uses two long short-term memories (LSTM). [21] Its architecture consists of two parts. The encoder is an LSTM that takes in a sequence of tokens and turns it into a vector. The decoder is another LSTM that converts the vector into a sequence

  8. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Format Default Task Created (updated) Reference Creator NYSK Dataset English news articles about the case relating to allegations of sexual assault against the former IMF director Dominique Strauss-Kahn. Filtered and presented in XML format. 10,421 XML, text Sentiment analysis, topic extraction 2013 [24] Dermouche, M. et al.

  9. File:Example.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Example.pdf

    Short title: example derived form Ghostscript examples: Image title: derivative of Ghostscript examples "text_graphic_image.pdf", "alphabet.ps" and "waterfal.ps"