Theoretical questions in Neural and Evolutionary Computing
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Universal Approximation Theorem — Neural Networks
I posted this earlier on MSE, but it was suggested that here may be a better place to ask.
Universal approximation theorem states that "the standard multilayer feed-forward network with a single ...
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0answers
28 views
Regarding the probability of population in neural network training sets
With regards to my question title, if I am training a standard 2-x-1 neural network and I have a set of example values such as inputs = {0,0} ideal input = {0}, will the modification of the ...
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1answer
72 views
When to apply soft constraints evaluation functions in genetic algorithms?
As stated in the question, say i created a random population of 100 timetables. 1 % of these timetables are valid. Then, if I apply the soft constraints evaluation functions on the 1% valid ...
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1answer
238 views
To what extent is it possible to use genetic algorithms to make wind mill turbine blades more efficient?
I recently watched this video on youtube. It featured someone explaining how he used genetic algorithms to improve the efficiency of wind mill turbines by finding the optimal shape for the blades. ...
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1answer
197 views
Neural Networks to classify accelerometer double taps
I'm building an application for Android devices that requires it to recognize, by accelerometer data, the difference between walking noise and double tapping it. I'm trying to solve this problem using ...
4
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2answers
167 views
Selection in a genetic algorithm
I have a working genetic algorithm which uses a few genetic operators on pairs of individuals.
These two individuals are selected by fitness-proportional (roulette-wheel) selection, that is, an ...
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2answers
255 views
Accuracy rate in neural networks
I've implemented a neural network (using the back-propagation algorithm) in a digital marketing application, where the algorithm classifies words according to quality, price and another ...
2
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1answer
125 views
Linear Function Representation of Neural Network
I have trained a neural network using MATLAB and am ready to deploy it into my software. Right now, I include it in my software by programming the structure of the neural network and the connection ...
2
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0answers
141 views
Computational power of cellular neural networks
A cellular neural network is a kind of recurrent neural network that could be thought of as a hybrid between neural nets and cellular automata.
As I understand it, the classic Chua-Yang CNN is ...
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1answer
102 views
What is the correct name for the space of genotypes and fitness?
I'm looking for a formal definition of the space that consists of the dimensions gene 1-N and the fitness.
In literature there is often the search space mentioned, but it only contains all genes. If ...
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2answers
521 views
Purpose and determining when to use hidden layers
Following up on this question...
I am attempting to learn how to use and create neural networks for my research, and one point is somewhat escaping me. I realize that hidden layers are a somewhat ...
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1answer
244 views
What are some examples of sequential-decision tasks?
I ask this because I'm currently learning about Neural Networks as a subset of the machine learning algorithms
Just trying to get some intuition on what sort of problems out there are categorized as ...
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0answers
48 views
Can we benefit the linear relation between $\sigma$ and best convergence speed in $(\mu,\lambda)$-ES and $(\mu+\lambda)$-ES?
$(\mu,\lambda)$-ES and $(\mu+\lambda)$-ES are two well-known Evolution Strategies. One variant of these algorithms is when we set a constant value for $\sigma$ and generate off-springs for $x$ as:
$$
...
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1answer
232 views
GA puzzle solver stuck at local maximum
I have a jigsaw type problem with 192 pieces which I am trying to find solutions to. I have written a GA which starts from a random allocation then 'crosses' by taking rectangular blocks from one ...
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2answers
294 views
What limits the performance of evolutionary computing techniques?
What limits the current performance of genetic algorithms and neural networks?
The principles underlying these techniques, at least the popular science presentation of these principles, suggests that ...
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2answers
188 views
Genetic Algorithm convergence test functions
I was working on parallel implementation of Genetic Algorithm with MapReduce. I have found that in many papers authors are referencing OneMAX as problem they used to test scalability and convergence ...
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2answers
292 views
Dealing with duplicates in Genetic Algorithm
I'm using Genetic Algorithm to create a rota for home-care organisation. All the groundwork is complete, I'm getting the results, but results are not as good as expected.
If I calculate fitness for ...
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2answers
197 views
Genetic algorithms
Is it theoretically possible to reconstruct the contents of a file from its id using evolutionary computing?
A file in this case can be a text, image, video or audio file.
The 'id' in this case, ...
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2answers
340 views
Quantum PAC learning
Background
Functions in $AC^0$ are PAC learnable in quasipolynomial time with a classical algorithm that requires $O(2^{log(n)^{O(d)}})$ randomly chosen queries to learn a circuit of depth d [1]. If ...
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1answer
522 views
How much computational power fits into a cubic centimeter?
This question is a followup on the question about DNA algorithms asked by Aadita Mehra.
In comments there, Joe Fitzsimmons said, in part:
[T]he radius of the system must scale proportionately to ...
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1answer
419 views
Computational Power of Neural Networks?
Let's say we have a single-layer feed forward neural network with k inputs and one output. It calculates a function from $\lbrace 0,1\rbrace ^{n}\rightarrow\lbrace 0,1\rbrace $, it's fairly easy to ...
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1answer
130 views
Analysis of variables of varying numbers
i work with amino acid sequences and i want to use a selfmade model to tell me something about it, lets call it f(seq). Now i want to know the contribution of every position in the sequence onto the ...
6
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2answers
426 views
What subjects, topics does a computer science graduate need to learn to apply available machine learning frameworks, esp. SVMs
I want to teach myself enough machine learning so that I can, to begin with, understand enough to put to use available open source ML frameworks that will allow me to do things like:
Go through the ...
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1answer
334 views
What does “number of inputs to each neuron” mean in Neural Network terms?
I am reading about a Neural Networks project that has some data like this
I am new to this, and though I think I understand what a 3:1 network mean, I do not understand what number of inputs (to ...
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10answers
2k views
Provable statements about genetic algorithms
Genetic algorithms don't get much traction in the world of theory, but they are a reasonably well-used metaheuristic method (by metaheuristic I mean a technique that applies generically across many ...
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2answers
606 views
What is schema theory within Genetic Algorithms
I understand (some) of the workings behind schema theory in genetic algorithms, for example:
*****0 would match the genome ...
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11answers
1k views
What are some real world applications for genetic algorithms?
What are some real world problems that have been solved using a genetic algorithm? What is the problem? What is the fitness test used to solve this problem?
