Questions tagged [neural-networks]

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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1answer
2k views

Is there a simple way of calculating perceptron weights based on a classification graph?

I am studying for an AI exam and I'm looking for a better way of solving the following problem: Graph shows a classification problem in the unit square $[0,1]^2$, where Class A is denoted by the ...
3
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2answers
151 views

Finding Feature Representation Such That Two Samples Are Similar in Feature Space

Consider one specific useful function of our human brain: abstraction of object. Take the example of two pictures: if we are told the pictures are similar, we actually make conclusion about the ...
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1answer
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How would a neural network deal with an arbitrary length output?

I've been looking into Recurrent Neural Networks, but I don't understand what the architecture of a neural network would look like when the output length is not necessarily fixed. It seems like most ...
9
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1answer
5k views

Could an artificial neural network algorithm be expressed in terms of map-reduce operations?

Could an artificial neural network algorithm be expressed in terms of map-reduce operations? I am also interested more generally in methods of parallelization as applied to ANNs and their application ...
16
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2answers
10k views

Must Neural Networks always converge?

Introduction Step One I wrote a standard backpropegating neural network, and to test it, I decided to have it map XOR. It is a 2-2-1 network (with tanh activation function) ...
10
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2answers
1k views

Is computational power of Neural networks related to the activation function

It is proven that neural networks with rational weights has the computational power of the Universal Turing Machine Turing computability with Neural Nets. From what I get, it seems that using real-...
10
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1answer
1k views

How many layers should a neural network have?

Are there any advantages of having more than 2 hidden layers in a Neural Network? I've seen some places that recommend it, others prove that there is no advantage. Which one is right?
19
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1answer
816 views

Efficiently computing or approximating the VC-dimension of a neural network

My goal is to solve the following problem, which I have described by its input and output: Input: A directed acyclic graph $G$ with $m$ nodes, $n$ sources, and $1$ sink ($m > n \geq 1$). Output: ...
29
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2answers
674 views

Why do neural networks seem to perform better with restrictions placed on their topology?

Fully connected (at least layer to layer with more than 2 hidden layers) backprop networks are universal learners. Unfortunately, they are often slow to learn and tend to over-fit or have awkward ...
8
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1answer
295 views

The essential difference between spiking neural networks and earlier generation ANN's

I have been studying Spiking Neural Networks online from various papers, mainly Maass (1997). I am not entirely sure I understand what makes SNN's pulse-code in contrast to earlier ANNs which are ...