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.

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19
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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
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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 ...
29
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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 ...
46
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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 ...
14
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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?
74
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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? ...
14
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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 ...
9
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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 ...
10
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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 ? ...
11
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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 ...
41
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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
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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 ...
27
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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
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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?
11
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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 ...
5
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3answers
708 views

Are neural networks statistical models?

By reading the abstract of Neural Networks and Statistical Models paper it would seem that ANNs are statistical models. In contrast Machine Learning is not just glorified Statistics. I am looking ...
9
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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?
11
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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 ...
8
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1answer
743 views

Mathematical intuition for the use of Re-Lu's in Machine Learning

So, currently the most commonly used activation functions are Re-Lu's. So I answered this question What is the purpose of an activation function in Neural Networks? and while writing the answer it ...
4
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4answers
379 views

What is the actual learning algorithm: back-propagation or gradient descent?

What is the actual learning algorithm: back-propagation or gradient descent (or, in general, the optimization algorithm)? I am reading through chapter 8 of Parallel Distributed Processing hand book ...
3
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1answer
90 views

Use cross-validation to train after model selection

I have been recently reading about model selection algorithms (for example to decide which value of the regularisation parameter or what size of a neural network to use, broadly hyper-parameters). ...
28
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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., ...
23
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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 ...
13
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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 ...
16
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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 ...
4
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1answer
315 views

Reinforcement Learning in asteroid game

Introduction An attractive asteroid game was described in the paper from 2007: quote: “In our first experiment, the virtual agent is a spaceship pilot, The pilot’s task is to maneuver the ...
10
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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 ...
7
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2answers
555 views

How can I start learning mathematics for machine learning?

I am an Android programmer. Now, I would like to learn machine learning. I know it requires a mathematical background, like statistics, probability, calculus and linear algebra. However, I am a bit ...
4
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2answers
286 views

What are different approaches used in Machine Learning?

There seem to be so many sub-fields, so I'm interested in getting a better understanding of the approaches. I'm looking for information on a single framework per answer, in order to allow for ...
9
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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 ...
4
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2answers
453 views

Why exactly do neural networks require i.i.d. data?

In reinforcement learning, in general, successive states (actions and rewards) are highly correlated. An "experience replay" buffer was used, in the DQN architecture, to avoid training the neural ...
4
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3answers
190 views

What kinds of problems can AI solve without using a deep neural network?

A lot of questions on this site seem to be asking "can I use X to solve Y?", where X is usually a deep neural network, and Y is often something already addressed by other areas of AI that are less ...
4
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3answers
253 views

Can someone direct me to a sites and/or videos that can bring an absolute beginner up to speed with AI?

To start, I'm not a programmer/computer scientist/et al... - I work in Finance and have, through my job, self-thought myself VBA for excel and outlook and would consider myself as being in the upper ...
3
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2answers
100 views

How can we specify AI field, respect to job positions?

I am interested to know, if someone wants to be an AI expert, what should he/she know, as we can see this is a vast field today! For example, if someone works on machine vision, should he/she know ...
3
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1answer
56 views

Combining different trained neural networks

I'm relatively new to this whole AI thing and have a question.. Let's say I have two different fully trained neural networks. The first one is trained for mathematical addition and the second one on ...
2
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3answers
468 views

Is there such a thing like the machine learning paradox?

O'Reilly recently published an article about the machine learning paradox. (link) What it says goes basically like this: no machine learning algorithm can be perfect. If it was, it means it is ...
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2answers
2k views

What is non-Euclidean data?

What is non-Euclidean data? Where does this type of data arises? Apparently, graphs and manifolds are non-Euclidean data. Why exactly is that the case? What is the difference between non-Euclidean and ...
1
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1answer
228 views

How do I restrict the neural network structure to be acyclic in NEAT?

I want my neural network structure to not have a circular/looping structure something similar like a directed acyclic graph (DAG). How do I do that?
9
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3answers
880 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 ...
7
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5answers
977 views

How can action recognition be achieved?

For example, I would like to train my neural network to recognize the type of actions (e.g. in commercial movies or some real-life videos), so I can "ask" my network in which video or movie (and at ...
5
votes
3answers
553 views

Use of machine learning for analyzing companies enlisted in stock market

Can current trends and tools, in the field of machine learning, replicate the complexity of financial market? If yes, then what are the tools available in this domain. Q. I am trying to build a model ...
4
votes
1answer
727 views

Traveling salesman problem variant: which algorithm to choose?

I have an industrial problem which I'm trying to cast as a Traveling Salesman problem (TSP) in 3D euclidian space. There are physical limitations which implies that some subpaths may or may not be ...
4
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2answers
549 views

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 ...
4
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1answer
837 views

Were the requirements to solve the Turing Test in “AI: A Modern Approach” foreseen by Alan Turing, or backfilled by Peter Norvig and Stuart Russell?

In Section 1.1 of Artificial Intelligence: A Modern Approach, it is stated that a computer which passes the Turing Test would need 4 capabilities, and that these 4 capabilities comprise most of the ...
3
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3answers
299 views

Which functions can't neural networks learn efficiently?

There are a lot of papers that show that neural networks can approximate a wide variety of functions. However, I can't find papers that show the limitations of NNs. What are the limitations of ...
2
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2answers
772 views

What's the role of bounding boxes in object detection?

I'm quite new to the field of computer vision and was wondering what are the purposes of having the boundary boxes in object detection. Obviously, it shows where the detected object is, and using a ...
0
votes
1answer
34 views

Use deep learning to rank video scenes

I'm new to machine learning and especially, deep learning. Given a video (and it's subtitle), I need to generate a 10-second summary out of this video. How can I use ML and DL to produce the most ...
8
votes
2answers
414 views

Does Monte Carlo Search (specifically used by AlphaZero) Qualify as Machine Learning?

To the best of my understanding, Monte Carlo Search is an alternative method to Minimax for searching a tree of nodes. It works by choosing a move (generally the one with the highest chance of being ...
6
votes
2answers
304 views

How can a neural network approximate all functions when the weights are not allowed to grow exponentially?

It has been proven in the paper "Approximation by Superpositions of a Sigmoidal Function" (by Cybenko, in 1989) that neural networks are universal function approximators. I have a related question. ...
4
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2answers
122 views

What is the best approach for writing a program to identify objects in a picture then crop them a specific way?

My works quality control department is responsible for taking pictures of our products at various phases through our QC process and currently the process goes: Take picture of product Crop the ...