Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

Filter by
Sorted by
Tagged with
74
votes
17answers
12k views

What is the difference between artificial intelligence and machine learning?

These two terms seem to be related, especially in their application in computer science and software engineering. Is one a subset of another? Is one a tool used to build a system for the other? ...
46
votes
7answers
25k views

Why is Python such a popular language in the AI field?

First of all, I'm a beginner studying AI and this is not an opinion oriented question or one to compare programming languages. I'm not saying that is the best language. But the fact is that most of ...
41
votes
3answers
27k views

How can neural networks deal with varying input sizes?

As far as I can tell, neural networks have a fixed number of neurons in the input layer. If neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a ...
37
votes
4answers
9k views

Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of ...
29
votes
3answers
17k views

Why is Lisp such a good language for AI?

I've heard before from computer scientists and from researchers in the area of AI that that Lisp is a good language for research and development in artificial intelligence. Does this still apply, with ...
28
votes
4answers
38k views

How to select number of hidden layers and number of memory cells in an LSTM?

I am trying to find some existing research on how to select the number of hidden layers and the size of these of an LSTM-based RNN. Is there an article where this problem is being investigated, i.e., ...
27
votes
9answers
5k views

Is artificial intelligence vulnerable to hacking?

The paper The Limitations of Deep Learning in Adversarial Settings explores how neural networks might be corrupted by an attacker who can manipulate the data set that the neural network trains with. ...
24
votes
2answers
811 views

How is a deep neural network different from other neural networks?

How is a neural network having the "deep" adjective actually distinguished from other similar networks?
23
votes
2answers
7k views

Is it possible to train a neural network incrementally?

I would like to train a neural network where the output classes are not (all) defined from the start. More and more classes will be introduced later based on incoming data. This means that, every time ...
22
votes
2answers
871 views

Are there any ongoing projects which use the Stack Exchange for machine learning?

Are there any ongoing AI projects which use the Stack Exchange for machine learning?
19
votes
4answers
5k views

How to handle invalid moves in reinforcement learning?

I want to create an AI which can play five-in-a-row/gomoku. As I mentioned in the title, I want to use reinforcement learning for this. I use policy gradient method, namely REINFORCE, with baseline. ...
17
votes
7answers
1k views

If digital values are mere estimates, why not return to analog for AI?

The impetus behind the twentieth century transition from analog to digital circuitry was driven by the desire for greater accuracy and lower noise. Now we are developing software where results are ...
16
votes
3answers
21k views

Understanding GAN loss function

I'm struggling to understand the GAN loss function as provided in Understanding Generative Adversarial Networks (a blog post written by Daniel Seita). In the standard cross-entropy loss, we have an ...
15
votes
1answer
318 views

Are search engines considered AI?

Are search engines considered AI because of the way they analyze what you search for and remember it? Or how they send you ads of what you've searched for recently? Is this considered AI or just ...
15
votes
2answers
3k views

Why has cross entropy become the classification standard loss function and not Kullbeck Leibler divergence?

Cross entropy is identical to the KL divergence plus entropy of target distribution. KL equals to zero when the two distributions are the same, which seems more intuitive to me than the entropy of the ...
15
votes
1answer
341 views

Differences between backpropagation techniques

Just for fun, I am trying to develop a neural network. Now, for backpropagation I saw two techniques. The first one is used here and in many other places too. What it does is: It computes the ...
14
votes
5answers
2k views

What is the difference between machine learning and deep learning?

Can someone explain to me the difference between machine learning and deep learning? Is it possible to learn deep learning without knowing machine learning?
14
votes
2answers
8k views

What is the time complexity for training a neural network using back-propagation?

Suppose that a NN contains $n$ hidden layers, $m$ training examples, $x$ features, and $n_i$ nodes in each layer. What is the time complexity to train this NN using back-propagation? I have a basic ...
14
votes
3answers
2k views

Permutation invariant neural networks

Given a neural network $f$ that takes as input $n$ data points: $x_1, \dots, x_n$. We say $f$ is permutation invariant if $$f(x_1 ... x_n) = f(pi(x_1 ... x_n))$$ for any permutation $pi$. ...
13
votes
2answers
890 views

When is deep learning overkill?

For example, for classifying emails as spam, is it worthwhile - from a time/accuracy perspective - to apply deep learning (if possible) instead of another machine learning algorithm? Will deep ...
13
votes
4answers
1k views

What activation function does the human brain use?

Does the human brain use a specific activation function? I've tried doing some research, and as it's a treshold for whether the signal is sent through a neuron or not, it sounds a lot like ReLU. ...
12
votes
5answers
18k views

Why does C++ seem less widely used in AI?

I just want to know why do Machine Learning engineers and AI programmers use languages like python to perform AI task and not C++ even though C++ is technically a more powerful language than python.
12
votes
2answers
1k views

How do generative adversarial networks work?

I am reading about generative adversarial networks (GANs) and I have some doubts regarding it. So far, I understand that in a GAN there are two different types of neural networks: one is generative ($...
12
votes
2answers
586 views

Should deep residual networks be viewed as an ensemble of networks?

The question is about the architecture of Deep Residual Networks (ResNets). The model that won the 1-st places at "Large Scale Visual Recognition Challenge 2015" (ILSVRC2015) in all five main tracks: ...
12
votes
4answers
225 views

What are some tactics for recognizing artificially made media?

With the growing ability to cheaply create fake pictures, fake soundbites, and fake video there becomes an increasing problem with recognizing what is real and what isn't. Even now we see a number of ...
11
votes
3answers
401 views

How would an AI learn language?

I was think about AIs and how they would work, when I realised that I couldn't think of a way that an AI could be taught language. A child tends to learn language through associations of language and ...
11
votes
2answers
8k views

What are bottleneck features?

In the blog post Building powerful image classification models using very little data, bottleneck features are mentioned. What are the bottleneck features? Do they change with the architecture that is ...
11
votes
3answers
360 views

What are the main problems hindering current AI development?

I have a background in Computer Engineering and have been working on developing better algorithms to mimic human thought. (One of my favorites is Analogical Modeling as applied to language processing ...
11
votes
1answer
182 views

What are all the different kinds of neural networks used for?

I found the following neural network cheat sheet (Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data). What are all these different kinds of neural networks used ...
11
votes
2answers
3k views

How to choose an activation function?

I choose the activation function for the output layer depending on the output that I need and the properties of the activation function that I know. For example, I choose the sigmoid function when I'm ...
11
votes
4answers
1k views

What are the latest methods to train a chat bot?

I would like to train a bot that uses text input, memorizes a few categories and answers questions accordingly. In addition as version 2.0, I want to make the bot to answer voice inputs as well. Which ...
10
votes
3answers
467 views

How does noise affect generalization?

Does increasing the noise in data help to improve the learning ability of a network? Does it make any difference or does it depend on the problem being solved? How is it affect the generalization ...
10
votes
2answers
131 views

What does it mean for a neuron in a neural network to be activated?

I just stumbled upon the concept of neuron coverage, which is the ratio of activated neurons and total neurons in a neural network. But what does it mean for a neuron to be "activated"? I know what ...
10
votes
2answers
578 views

The Singularity and future of civilisation

My understanding of the singularity is when artificial intelligence becomes "more intelligence" than humans. This will be achieved through machine learning where an; algorithm, neural network ? ...
10
votes
3answers
10k views

Measuring Object size using Deep Neural Network

I have a large dataset of vehicles with the ground truth of their lengths (Over 100k samples). Is it possible to train a deep network to measure/estimate vehicle length ? I haven't seen any papers ...
10
votes
1answer
345 views

AI that can generate programs

I have been looking into Viv an artificial intelligent agent in development. Based on what I understand, this AI can generate new code and execute it based on a query from the user. What I am curious ...
10
votes
3answers
1k views

Using neural network to recognise patterns in matrices

I am trying to develop a neural network which can identify design features in CAD models (i.e. slots, bosses, holes, pockets, steps). The input data I intend to use for the network is a n x n matrix (...
10
votes
4answers
191 views

How do I select the relevant features of the data?

Recently I was working on a problem to do some cost analysis of my expenditure for some particular resource. I usually make some manual decisions from the analysis and plan accordingly. I have a big ...
10
votes
1answer
823 views

Are information processing rules from gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
9
votes
3answers
8k views

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
9
votes
4answers
229 views

What are the domains where SVMs are still state-of-the-art?

It seems that deep neural networks and other neural network based models are dominating many current areas like computer vision, object classification, reinforcement learning, etc. Are there domains ...
9
votes
6answers
837 views

What do I need to study for machine learning?

Starting from last year, I have been studying various subjects in order to understand some of the most important thesis of machine learning like S. Hochreiter, & J. Schmidhuber. (1997). Long ...
9
votes
3answers
881 views

What are the purposes of autoencoders?

Autoencoders are neural networks that learn a compressed representation of the input in order to later reconstruct it, so they can be used for dimensionality reduction. They are composed of an encoder ...
9
votes
1answer
4k views

How to transform inputs and extract useful outputs in a Neural Network?

So I've been trying to understand neural networks ever since I came across Adam Geitgey's blog on machine learning. I've read as much as I can on the subject (that I can grasp) and believe I ...
9
votes
1answer
214 views

How to stay a up-to-date researcher in ML/RL community?

As a student who wants to work on machine learning, I would like to know how it is possible to start my studies and how to follow it to stay up-to-date. For example, I am willing to work on RL and MAB ...
9
votes
2answers
4k views

Can AI write good jokes yet?

Just watched a recent WIRED video on virtual assistants' performance on telling jokes. They're composed by humans, but I'd like to know if AI has gotten good enough to write some.
9
votes
1answer
2k views

Selecting the right technique to predict disease from symptoms

I'm trying to come up with the right algorithm for a system in which the user enters a few symptoms and the system has to predict or determine the likelihood that a few selected symptoms are ...
9
votes
4answers
8k views

Teach a Neural Network to play a card game

I am currently writing an engine to play a card game, as there is no engine yet for this particular game. I am hoping to be able to introduce a neural net to the game afterwards, and have it learn to ...
9
votes
4answers
2k views

How does using ASIC for the acceleration of AI work?

We can read on Wikipedia page that Google built a custom ASIC chip for machine learning and tailored for TensorFlow which helps to accelerate AI. Since ASIC chips are specially customized for one ...
9
votes
1answer
2k views

Loss jumps abruptly when I decay the learning rate with Adam optimizer in PyTorch

I'm training an auto-encoder network with Adam optimizer (with amsgrad=True) and ...