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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807 views

Adapting neural network

I have on a few occasions trained neural networks (back propagation networks) with some rather complicated data sets (backgammon positions and OCR). When doing this, it seems that a lot of the work ...
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What can be learned from the weights in a neural network?

I'm very new to neural networks, and have been trying to figure some things out. So, let's say you come across a neural network which has 100 inputs, a hidden layer with 200 nodes, and 32 outputs. ...
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About the behaviour of multi-layer perceptrons

I have a multilayer perceptron. It has an input layer with two neurons, a hidden layer with an arbitrary number of neurons, and an output layer with two neurons. Given that ...
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1answer
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Neural Network weight selection using Genetic Algorithm

Hi I want to ask about weight selection in neural network using genetic algorithm. Right now what I understand is Initialize population Encode the weight of the neural network to the chromosome ...
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411 views

What factors must one consider choosing an NN structure?

Suppose we have a classification problem and we wish to solve the problem by Neural Network. What factors must one consider choosing an NN structure? e.g Feed Forward, Recurrent and other available ...
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What's the difference between a rule based system and an artificial neural network?

I'm currently doing some reading into AI and up to this point couldn't find a satisfying answer to this question: what's the difference between a rule based system and an artificial neural network? ...
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What piece am I missing to turn this idea into a programming language?

I've been doing some reading (I'll name drop along the way) and have selected a few scattered ideas that I think could be cobbled together into a nifty esoteric programming language. But I'm having ...
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1answer
626 views

How to compare the output of a neural network with his target?

I am coding a neural network implementation, but a I have problems in the design. I was wondering about how to compare the output with the target, my neural networks has three outputs ...
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3k 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 ...
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154 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 ...
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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 ...
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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) ...
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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-...
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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?
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980 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: ...
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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 ...
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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 ...

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