Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

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Why did fuzzy logic fall out of fashion?

Fuzzy logic seemed like an active area of research in machine learning and data mining back when I was in grad school (early 2000s). Fuzzy inference systems, fuzzy c-means, fuzzy versions of the various neural network and support vector machine…
Alex S King
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Why did the L1/L2 regularization technique not improve my accuracy?

I am training a multilayer neural network with 146 samples (97 for the training set, 20 for the validation set, and 29 for the testing set). I am using: automatic differentiation, SGD method, fixed learning rate + momentum term, logistic…
LVoltz
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Can artificial intelligence applications be hacked?

Can artificial intelligence (or machine learning) applications or agents be hacked, given that they are software applications, or are all AI applications secure?
ME.
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How to constraint the output value of a neural network?

I am training a deep neural network. There is a constraint on the output value of the neural network (e.g. the output has to be between 0 and 180). I think some possible solutions are using sigmoid, tanh activation at the end of the layer. Are there…
raemoii
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Which model should I use to determine the similarity between predefined sentences and new sentences?

The Levenshtein algorithm and some ratio and proportion may handle this use case. Based on the pre-defined sequence of statements, such as "I have a dog", "I own a car" and many more, I must determine if an another input statement such as "I have a…
alona
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Does overfitting imply an upper bound on model size/complexity?

Suppose that I have a model M that overfits a large dataset S such that the test error is 30%. Does that mean that there will always exist a model that is smaller and less complex than M that will have a test error less than 30% on S (and does not…
Shehryar Malik
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Which neural network to use for optical mark recognition?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer as the activation function layer. I'm using this…
Hamza Abdullah
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How can my Q-learning agent trained to solve a specific maze generalize to other mazes?

I implemented Q-learning to solve a specific maze. However, it doesn't solve other mazes. How could my Q-learning agent be able to generalize to other mazes?
lrosique
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What are the ways to calculate the error rate of a deep Convolutional Neural Network, when the network produces different results using the same data?

I am new to the object recognition community. Here I am asking about the broadly accepted ways to calculate the error rate of a deep CNN when the network produces different results using the same data. 1. Problem introduction Recently I was trying…
Daqi Dong
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Should the reward or the Q value be clipped for reinforcement learning

When extending reinforcement learning to the continuous states, continuous action case, we must use function approximators (linear or non-linear) to approximate the Q-value. It is well known that non-linear function approximators, such as neural…
Rui Nian
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How do I calculate the gradient of the hinge loss function?

With reference to the research paper entitled Sentiment Embeddings with Applications to Sentiment Analysis, I am trying to implement its sentiment ranking model in Python, for which I am required to optimize the following hinge loss function:…
Raj Shrivastava
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Traffic signs dataset

I'm looking for annotated dataset of traffic signs. I was able to find Belgium, German and many more traffic signs datasets. The only problem is these datasets contain only cropped images, like this: While i need (for YOLO -- You Only Look Once…
kocica
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How fast is TensorFlow compared to self written neural nets?

I made my first neural net in C++ without any libraries. It was a net to recognize numbers from the MNIST dataset. In a 784 - 784 - 10 net with sigmoid function and 5 epochs with every 60000 samples, it took about 2 hours to train. It was probably…
Evator
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How does L2 regularization make weights smaller?

I'm learning logistic regression and $L_2$ regularization. The cost function looks like below. $$J(w) = -\displaystyle\sum_{i=1}^{n} (y^{(i)}\log(\phi(z^{(i)})+(1-y^{(i)})\log(1-\phi(z^{(i)})))$$ And the regularization term is added. ($\lambda$ is a…
Riddle Aaron
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Do good approximations produce good gradients?

Let’s say I have a neural net doing classification and I’m doing stochastic gradient descent to train it. If I know that my current approximation is a decent approximation, can I conclude that my gradient is a decent approximation of the gradient of…
Stella Biderman
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