Can anyone give me any rapid explanation?
ELM is learning mechanism for providing solutions for generalized Feed-forward networks. ELM states that nodes and neurons in the hidden layers can be randomly generated.
http://www.ntu.edu.sg/home/egbhuang/index.html
With tied weight i mean the Weight matrix of the decoder is the transopse of the weight matrix of the encoder.
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Usually (as far as i now) Bernoulli-Bernoulli RBM are used in a DBN to make higher level binary features. Is there any work that tried to make these features continued values?
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