Artificial Intelligence Stack Exchange
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How to use CNN for making predictions on non-image data?

I have a dataset which I have loaded as a data frame in Python. It consists of 21392 rows (the data instances, each row is one sample) and 1972 columns (the features). The last column i.e. column 1972 has string type labels (14 different categories…
JChat
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Can artificial intelligence be thought of as optimization?

In this video an expert says, "One way of thinking about what intelligence is [specifically with regard to artificial intelligence], is as an optimization process." Can intelligence always be thought of as an optimization process, and can artificial…
dynrepsys
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Is the expert system still in use today?

In my country, the Expert System class is mandatory, if you want to take the AI specialization in most universities. In class, I learned how to make a rule-based system, forward chaining, backward chaining, Prolog, etc. However, I have read…
malioboro
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Is it possible to use AI to reverse engineer software?

I was thinking of something of the sort: Build a program (call this one fake user) that generates lots and lots and lots of data based on the usage of another program (call this one target) using stimuli and response. For example, if the target is…
IpsumPanEst
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What happens when I mix activation functions?

There are several activation functions, such as ReLU, sigmoid or $\tanh$. What happens when I mix activation functions? I recently found that Google has developed Swish activation function which is (x*sigmoid). By altering activation function can it…
JSChang
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Can someone help me to understand the alpha-beta pruning algorithm?

I understand the minimax algorithm, but I am unable to understand deeply the minimax algorithm with alpha-beta pruning, even after having looked up several sources (on the web) and having tried to read the algorithm and understand how it works. Do…
Sunshine
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What is the concept of channels in CNNs?

I am trying to understand what channels mean in convolutional neural networks. When working with grayscale and colored images, I understand that the number of channels is set to 1 and 3 (in the first conv layer), respectively, where 3 corresponds to…
anonuser01
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Why does the "reward to go" trick in policy gradient methods work?

In the policy gradient method, there's a trick to reduce the variance of policy gradient. We use causality, and remove part of the sum over rewards so that only actions happened after the reward are taken into account (See here…
Konstantin Solomatov
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Is it possible to clean up an audio recording of a lecture using some type of AI system?

Is it possible to clean up an audio recording of a lecture from a smartphone (i.e. remove the background noise) using some type of AI system?
Thibault Molleman
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Do GANs come under supervised learning or unsupervised learning?

Do GANs come under supervised learning or unsupervised learning? My guess is that they come under supervised learning, as we have labeled dataset of images, but I am not sure as there might be other aspects in GANs which might come into play in the…
codecracker
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Why is the variational auto-encoder's output blurred, while GANs output is crisp and has sharp edges?

I observed in several papers that the variational autoencoder's output is blurred, while GANs output is crisp and has sharp edges. Can someone please give some intuition why that is the case? I did think a lot but couldn't find any logic.
Trect
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Why is baseline conditional on state at some timestep unbiased?

In the homework for the Berkeley RL class, problem 1, it asks you to show that the policy gradient is still unbiased if the baseline subtracted is a function of the state at time step $t$. $$ \triangledown _\theta \sum_{t=1}^T \mathbb{E}_{(s_t,a_t)…
Laura C
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How do you program fear into a neural network?

If you've been attacked by a spider once, chances are you'll never go near a spider again. In a neural network model, having a bad experience with a spider will slightly decrease the probability you will go near a spider depending on the learning…
zooby
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What is a support vector machine?

What is a support vector machine (SVM)? Is an SVM a kind of a neural network, meaning it has nodes and weights, etc.? What is it best used for? Where I can find information about these?
Efthymios Kalyviotis
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What is the relationship between these two taxonomies for machine learning with neural networks?

Could you please let me know which of the following classification of Neural Network's learning algorithm is correct? The first one classifies it into: supervised, unsupervised and reinforcement learning. However, the second one provides a…
ebrahimi
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