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Network structure inspired by simplified models of biological neurons (brain cells). Neural networks are trained to "learn" by supervised and unsupervised techniques, and can be used to solve optimization problems, approximation problems, classify patterns, and combinations thereof.
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votes
1
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23
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Intersection of two generative neural networks
I have an input x (a word), and I have a neural network Y such that Y(x), which is an image always satisfies F(x), and another neural network Z such that Z(x), which is also an image, always satisfies …
4
votes
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answers
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How to represent sentences with their dependency parses as input to an RNN?
I am working on a task embedding sentences into a lower-dimensional space according to style, both grammatical and lexical. As such, I want to have as input the linear ordering of tokens in each sent …
1
vote
1
answer
467
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Is deep learning appropriate to approximate dynamic programming problems?
I have a problem which can be completely solved using dynamic programming, but in a very intractable way (On^4, where n is around 1000). I won't get into the details of the problem since it's a bit c …