enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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. 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]

  4. Sepp Hochreiter - Wikipedia

    en.wikipedia.org/wiki/Sepp_Hochreiter

    Hochreiter developed the long short-term memory (LSTM) neural network architecture in his diploma thesis in 1991 leading to the main publication in 1997. [3] [4] LSTM overcomes the problem of numerical instability in training recurrent neural networks (RNNs) that prevents them from learning from long sequences (vanishing or exploding gradient).

  5. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    LSTM works even given long delays between significant events and can handle signals that mix low and high-frequency components. Many applications use stacks of LSTMs, [57] for which it is called "deep LSTM". LSTM can learn to recognize context-sensitive languages unlike previous models based on hidden Markov models (HMM) and similar concepts. [58]

  6. Types of artificial neural networks - Wikipedia

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

    Memory networks [69] [70] incorporate long-term memory. 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]

  7. Sylvester Stallone Says He Was a 'Coward' for FedExing ... - AOL

    www.aol.com/lifestyle/sylvester-stallone-says...

    Stallone, 78, and Flavin, 56, sat down with Sean Hannity for the inaugural Dec. 3 episode of Fox Nation's new long-form interview show, Sean, during which the Rocky star confirmed that he did ...

  8. Lawsuit accuses major food companies of marketing 'addictive ...

    www.aol.com/news/lawsuit-accuses-major-food...

    (Reuters) -Major food companies, including Kraft Heinz, Mondelez and Coca-Cola, were hit with a new lawsuit in the U.S. on Tuesday accusing them of designing and marketing "ultra-processed" foods ...

  9. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Studies considered long-and short-term plasticity of neural systems and their relation to learning and memory from the individual neuron to the system level. It is possible to create a profile of a user's interests from pictures, using artificial neural networks trained for object recognition. [209]