Questions tagged [terminology]

For questions related to the definition of and use of terminology in the context of Artificial Intelligence

Filter by
Sorted by
Tagged with
2
votes
1answer
41 views

What are episodic and non-episodic domains in reinforcement learning?

I was reading about the temporal difference (TD) learning and I read that: TD handles continuing, non-episodic domains Assuming that continuing means non-terminating, what does non-episodic or ...
27
votes
6answers
47k views

What is the difference between a convolutional neural network and a regular neural network?

I've seen these terms thrown around this site a lot, specifically in the tags convolutional-neural-networks and neural-networks. I know that a neural network is a system based loosely on the human ...
1
vote
5answers
172 views

What is machine learning?

What is the definition of machine learning? What are the advantages of machine learning?
8
votes
5answers
495 views

What is “backprop”?

What does "backprop" mean? Is the "backprop" term basically the same as "backpropagation" or does it have a different meaning?
1
vote
2answers
131 views

Who first coined the term “artificial general intelligence”?

Similarly to the question Who first coined the term Artificial Intelligence?, who first coined the term "artificial general intelligence"?
10
votes
3answers
223 views

What is a deep neural network?

What is the definition of a deep neural network? Why are they so popular or important?
4
votes
5answers
204 views

What is an artificial neural network?

What is an artificial neural network in artificial intelligence? It is apparently used to find patterns in data and it is loosely inspired by human neural networks.
11
votes
2answers
2k views

Who first coined the term Artificial Intelligence?

Who first coined the term Artificial Intelligence? Is there a published research paper that first used that term?
1
vote
1answer
79 views

What is teacher forcing?

In the paper Neural Programmer-Interpreters, the authors use the teacher forcing technique, but what exactly is it?
10
votes
4answers
1k views

What does “stationary” mean in the context of reinforcement learning?

I think I've seen the expressions "stationary data", "stationary dynamics" and "stationary policy", among others, in the context of reinforcement learning. What does it mean? I think stationary policy ...
2
votes
2answers
75 views

Is my understanding of the value function, Q function, policy, reward and return correct?

I'm a beginner in the RL field, and I would like to check that my understanding of certain RL concepts. Value function: How good it is to be in a state S following policy π. ...
5
votes
1answer
170 views

What is a weighted average in a non-stationary k-armed bandit problem?

In the book Reinforcement Learning: An Introduction (page 25), by Richard S. Sutton and Andrew G. Barto, there is a discussion of the k-armed bandit problem, where the expected reward from the bandits ...
1
vote
2answers
66 views

Is the Q value the same as the state-action pair value?

Am I right to say that the Q value of a particular state and action is the same as the state-action pair value of that same state and action?
1
vote
1answer
36 views

What is it called in AI when a program is designed to make “x in the style of y”?

Simplified: What is it called in AI when a program is designed to make "x in the style of y;" when it trains off of two types of sources in order to make a thing from source one, informed by features ...
4
votes
1answer
1k views

How can I understand this statement about RNNs and hidden layers?

In the lecture, there was a statement: Recurrent neural networks with multiple hidden layers are just a special case that has some of the hidden to hidden connections missing. I understand ...
1
vote
1answer
48 views

What do these numbers represent in this picture of a surface?

The following image is a screenshot from a video tutorial that illustrates the concept of gradient descent algorithm with a 3D animation. Do the numbers on the top of the balls pointed out by the red ...
1
vote
1answer
45 views

What is “natural image domain”?

I see some papers use the term "natural image domain". I googled that but didn't find any explanation of it. I guess I understand the normal meaning of "natural image", such as the image people take ...
2
votes
1answer
61 views

What are “proxy data sets” in machine learning?

The paper Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration uses the term "proxy data sets" in this way To develop DL ...
1
vote
1answer
50 views

What is a landmark in computer vision?

I guess I understand the concept of face detection, a technique specifies the location of multiple objects in the image, and draws bounding boxes on the target. The question is related to the concept ...
2
votes
2answers
101 views

Why is it called back-propagation?

While looking at the mathematics of the back-propagation algorithm for a multi-layer perceptron, I noticed that in order to find the partial derivative of the cost function with respect to a weight (...
3
votes
2answers
546 views

What is the difference between learning without forgetting and transfer learning?

I would like to incrementally train my model with my current dataset and I asked this question on Github issues, which is what I'm using SSD MobileNet v1: https://github.com/tensorflow/models/issues/...
3
votes
1answer
50 views

What is the type of problem requiring to rate images on a scale?

I'm new to the topic, but I've used some off the shelf knowledge about computer vision for classifying images. For example, you can easily generate labels that can determine whether or not e.g. a ...
4
votes
3answers
151 views

What does end-to-end training mean?

In simple words, what does end-to-end training mean, in the context of deep learning?
5
votes
1answer
2k views

What is the difference between search and planning?

I'm studying Artificial Intelligence. A Modern Approach, Stuart Russell, Peter Norvig, specifically about search and planning arguments. I don't understand the difference between the two terms. I was ...
1
vote
1answer
44 views

What is “temporal depth”?

I need some explanation about the following paragraph (page 3) from the paper A Novel Approach for Robust Multi Human Action Detection and Recognition based on 3-Dimentional Convolutional Neural ...
1
vote
1answer
42 views

What is an end-to-end AI project?

I often read about the so-called end-to-end AI (or analytics) projects, but I couldn't find a definition of it. What is an end-to-end AI project? Can someone explain what is meant/expected when ...
1
vote
1answer
52 views

Are there names for neural networks with a well-defined layer or neuron characteristics?

Are there names for neural networks with a well-defined layer or neuron characteristics? For example, a matrix that has the same number of rows and columns is called a square matrix. Is there an ...
2
votes
2answers
77 views

What is the name of this neural network architecture with layers that are also connected to non-neighbouring layers?

Consider a feedforward neural network. Suppose you have a layer of inputs, which is feedforward to a hidden layer, and feedforward both the input and hidden layers to an output layer. Is there a name ...
4
votes
2answers
178 views

What is “Computational Linguistics”?

It's not clear to me whether or not someone whose work aims to improve an NLP system may be called a "Computational Linguist" even when she/he doesn't modify the algorithm directly by coding. Let's ...
1
vote
1answer
56 views

Is the following statement about neural networks overclaimed?

Is the following statement about neural networks overclaimed? Neural networks are iterative methods that minimize a loss function defined on the output layer of neurons. I wrote this statement in ...
2
votes
1answer
439 views

Are model-free and off-policy algorithms the same?

In respect of RL, is model-free and off-policy the same thing, just different terminology? If not, what are the differences? I've read that the policy can be thought of as 'the brain', or decision ...
3
votes
2answers
76 views

Why are the terms classification and prediction used as synonyms in the context of deep learning?

Why are the terms classification and prediction used as synonyms especially when it comes to deep learning? For example, a CNN predicts the handwritten digit. To me, a prediction is telling the next ...
2
votes
2answers
60 views

What does “immediate vector-valued feedback” mean?

In the book Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning, James Stone says With supervised learning, the response to each input vector is an output ...
3
votes
1answer
34 views

What is the difference between the concepts “known environment” and “deterministic environment”?

According to the book "Artificial Intelligence: A Modern Approach", "In a known environment, the outcomes (or outcome probabilities if the environment is stochastic) for all actions are given.", and ...
2
votes
0answers
125 views

What does “episodic training” mean?

I'm reading the book Hands-On Meta Learning with Python, and in Prototypical networks said: So, we use episodic training—for each episode, we randomly sample a few data points from each class in ...
9
votes
3answers
3k views

What is a “trajectory” in reinforcement learning?

I'm now learning about reinforcement learning, but I just found the word "trajectory" in this answer. However, I'm not sure what it means. I read a few books on the Reinforcement Learning but none of ...
10
votes
2answers
3k views

What is the difference between artificial intelligence and computational intelligence?

Having analyzed and reviewed a certain amount of articles and questions, apparently, the expression computational intelligence (CI) is not used consistently and it is still unclear the relationship ...
2
votes
1answer
59 views

Are CNN, LSTM, GRU and transformer AGI or computational intelligence tools?

Will CNN, LSTM, GRU and transformer be better classified as Computational Intelligence (CI) tools or Artificial General Intelligence (AGI) tools? The term CI arose back when some codes like neural ...
2
votes
0answers
39 views

What role do distractors play in natural language processing?

I’m doing research on natural language processing (NLP). I’d like to put together my own model. However, I'm running into a concept I am not familiar with, namely, distractors. A google search does ...
1
vote
0answers
27 views

What is the term for an RNN that is a completely connected directed graph?

There seems to be a severe problem with the taxonomy of neural network topologies. What I'd like to know is the term I should use to search for the most general topology: completely connected ...
6
votes
2answers
332 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 ...
0
votes
1answer
92 views

What are the characteristics of a deep learning AI?

I have experience in making several Artificial Neural Networks and some programs which may be classified as an Artificial Intelligence by using Tensorflow.js and Brain.js. In order to produce ...
27
votes
7answers
14k views

How can an AI train itself if no one is telling it if its answer is correct or wrong?

I am a programmer but not in the field of AI. A question constantly confuses me is that how can an AI be trained if we human beings are not telling it its calculation is correct? For example, news ...
7
votes
1answer
2k views

What is the difference between memetic algorithms and genetic algorithms?

What is the difference between memetic algorithms and genetic algorithms? Is an individual's lifetime a learning part of memetic algorithms?
1
vote
2answers
154 views

What is the difference between a learning algorithm and a hypothesis?

What's the distinction between a learning algorithm $A$ and a hypothesis $f$? I'm looking for a few concrete examples, if possible. From what I understand, one way to vary the hypothesis $f$ would be ...
3
votes
2answers
1k views

What is a “surrogate model”?

In the following paragraph from the book Automated Machine Learning: Methods, Systems, Challenges (by Frank Hutter et al.) In this section we first give a brief introduction to Bayesian ...
5
votes
1answer
323 views

What is the “semantic level”?

I am reading the paper Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction (2018) by Yunzhe Tao et al. In this paper, they use several times the expression "semantic ...
3
votes
2answers
99 views

Why do we need learning in unsupervised learning? [duplicate]

I am not clear with the concept that an unsupervised model learns. We are giving an input and output to the supervised model, so that it can generate a particular value, pattern or something out of it ...
5
votes
1answer
272 views

What is “conditioning” on a feature?

On page 98 of Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning the author writes; Redacted phase space: Studying the distribution of inputs ...
4
votes
1answer
71 views

Why does a Lipschitz continuous discriminator in GANs assure statistical boundedness?

I have been reading the paper which introduced spectral normalization in GANs. At some point the paper mentions the following: The machine learning community has been pointing out recently that ...