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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. Gated recurrent unit - Wikipedia

    en.wikipedia.org/wiki/Gated_recurrent_unit

    Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al. [1] The GRU is like a long short-term memory (LSTM) with a gating mechanism to input or forget certain features, [2] but lacks a context vector or output gate, resulting in fewer parameters than LSTM. [3]

  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. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    The long-term memory can be read and written to, with the goal of using it for prediction. These models have been applied in the context of question answering (QA) where the long-term memory effectively acts as a (dynamic) knowledge base and the output is a textual response. [71]

  6. Banks, investors hope for lighter regulations after Fed's ...

    www.aol.com/banks-investors-hope-lighter...

    Girding for a possible battle in the courts, Barr recently sought advice from law firm Arnold & Porter, a Fed spokesperson said. Bartlett Naylor, financial policy advocate for Public Citizen, a ...

  7. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    An LSTM with a forget gate essentially functions as a highway network. To stabilize the variance of the layers' inputs, it is recommended to replace the residual connections x + f ( x ) {\displaystyle x+f(x)} with x / L + f ( x ) {\displaystyle x/L+f(x)} , where L {\displaystyle L} is the total number of residual layers.

  8. Ex-FBI informant pleads guilty to making false bribery ... - AOL

    www.aol.com/news/ex-fbi-informant-pleads-guilty...

    A former FBI informant pleaded guilty Monday to providing false information to federal authorities about Joe Biden and his son Hunter Biden months before the 2020 presidential election. Alexander ...

  9. What Experts Want You to Know About Dry January Health ... - AOL

    www.aol.com/experts-want-know-dry-january...

    To accomplish a month-long commitment like Dry January, people must prepare their environment and set themselves up for success, continues Dr. Miller. Take stock of what is in the pantry.