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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20
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4answers
6k 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. ...
18
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7answers
2k 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 ...
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3answers
18k 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 ...
49
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8answers
28k 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 implying that Python is the best language. But the fact is that ...
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?
78
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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? ...
15
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2answers
9k 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
948 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 ...
38
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4answers
10k 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 ...
11
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2answers
4k 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
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3answers
404 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 ...
47
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3answers
30k 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 ...
28
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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. ...
25
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2answers
941 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?
14
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3answers
12k views

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
5
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1answer
1k 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 ...
8
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1answer
375 views

What are the implications of the “No Free Lunch” theorem for machine learning?

The No Free Lunch (NFL) theorem states (see the paper Coevolutionary Free Lunches by David H. Wolpert and William G. Macready) any two algorithms are equivalent when their performance is averaged ...
11
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3answers
373 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
817 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
422 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
101 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
42k 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
8k 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 ...
14
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2answers
929 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 ...
11
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1answer
268 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 ...
16
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3answers
22k 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
348 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
11k 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
596 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 ...
5
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2answers
296 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 ...
5
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2answers
664 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
258 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 ...
4
votes
3answers
197 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 ...
3
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1answer
61 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
499 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 ...
2
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1answer
39 views

Should I remove the units of a neural network or increase dropout?

When adding dropout to a neural network, we are randomly removing a fraction of the connections (setting those weights to zero for that specific weight update iteration). If the dropout probability is ...
1
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1answer
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
250 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
1k 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
2answers
459 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 ...
8
votes
2answers
284 views

Can machine learning be used to pass the Turing test?

Can we say that the Turing test aims to develop machines or methods to reach human-level performance in all cognitive tasks and that machine learning is one of these methods that can pass the Turing ...
7
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5answers
1k 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
557 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 ...
5
votes
1answer
886 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 ...
4
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2answers
714 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
738 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 ...
3
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2answers
323 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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1answer
41 views

Three step threshold in Facenet model of face recogniton

Suppose i trained the images of two people say Bob , Thomas .When i run the algorithm to detect the face of a totally different person from these two say John , then John is recognized as Bob or ...
2
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1answer
81 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...