Questions tagged [terminology]

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

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2answers
48 views

What does “semantic gap” mean?

I was reading DT-LET: Deep transfer learning by exploring where to transfer, and it contains the following: It should be noted direct use of labeled source domain data on a new scene of target domain ...
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1answer
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What does “statistical efficiency” mean in this context?

Consider the following statement(s) from Deep Learning book (p. 333, chapter 9: Convolutional Networks) Convolution is thus dramatically more efficient than dense matrix multiplication in terms of ...
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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 ...
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26 views

Does Yann LeCun consider k-means self-supervised learning?

I was discussing the topic of self-supervised learning with a colleague. After a while we realized we were using different definitions. That's never helpful. Both of us were introduced to self-...
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3answers
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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 ...
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What part of the Vaswani et al. is the “transformer”?

Which part of this is the transformer? Ok, the caption says the whole thing is the transformer, but that's back in 2017 when the paper was published. My question is about how the community uses the ...
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1answer
74 views

Is the bias also a “weight” in a neural network?

I'm learning about how neural networks are trained. I understand how a neuron works, backpropagation, and all that. In neurons, there is a clear distinction between a "weight" and a "...
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What to use as a proxy for AI [closed]

Im trying to build a model using AI and the economy and only came my head to use patents as a proxy, do you guys know what else i can use as proxy for AI. I thought about using data from ...
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1answer
35 views

What is the difference between environment states and agent states in terms of Markov property?

I'm going through the David Silver RL course on YouTube. He talks about environment internal state $S^e_t$, and agent internal state $S^a_t$. We know that state $s$ is Markov if $\mathbb{P}\{S_t=s|S_{...
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1answer
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Must all CNNs and RNNs not have a fully connected layer in order to be considered as such?

In the paper Wrist-worn blood pressure tracking in healthy free-living individuals using neural networks, the authors talk about a combination of feed-forward and recurrent layers, as if FC layers ...
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755 views

What are the major differences between cost, loss, error, fitness, utility, objective, criterion functions?

I find the terms cost, loss, error, fitness, utility, objective, criterion functions to be interchangeable, but any kind of minor difference explained is appreciated.
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What does the term “closed expression” mean?

In the field of logic systems there is a property for reasoning algorithms called incompleteness or incompletion. In this context the phrase "any closed expression that is not derivable inside the ...
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What is the purpose of an activation function in neural networks?

It is said that activation functions in neural networks help introduce non-linearity. What does this mean? What does non-linearity mean in this context? How does the introduction of this non-...
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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? ...
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498 views

What is the difference between abstract, autonomous and virtual intelligent agents?

On Wikipedia, we can read about different type of intelligent agents: abstract intelligent agents (AIA), autonomous intelligent agents, virtual intelligent agent (IVA), which I've found on other ...
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6answers
2k views

What is fuzzy logic?

I'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?
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1answer
660 views

What's the definition of “singularity” in the context of neural networks?

The paper Skip connections eliminate singularities explains the use of skip connections to break the singularity in deep networks, but I have not fully understood what a singularity is. Any easy-...
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In Probabilistic Graphical Model (written by Daphne Koller), what's the meaning of “parameter” in representation of the distribution?

I just started to read the PGM book written by Daphne Koller. In the chapter of Bayesian Network Representation(Chapter 3), there are some descriptions about the standard parameterization of the joint ...
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1answer
27 views

Does a trajectory in reinforcement learning contain the last action?

From what I learn from CS285 and OpenAI's spinning up, a trajectory in RL is a sequence of state-action pairs: $$\tau = \{s_0, a_0, ..., s_t, a_t\}$$ And the resulting trajectory probability is: $$ P(\...
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56 views

What is the reason for taking tuples as vectors rather than points?

Across the literature of artificial intelligence, especially machine learning, it is normal to treat the tuples of datasets as vectors. Although there is a convention to treat them as data points. ...
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Why does self-supervised representation learning (such as SimpleSiam) use a ResNet encoder that is trained in a supervised fashion?

Can anybody explain to me why does self-supervised representation learning on images using Siamese neural networks (such as SimpleSiam (https://arxiv.org/abs/2011.10566), SimCLR, Boyl) use a ResNet ...
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1answer
79 views

Why are “Transformers” called this way?

What is the reason behind the name "Transformers", for Multi Head Self-Attention-based neural networks from Attention is All You Need? I have been googling this question for a long time, and ...
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What is the name of this algorithm that estimates the gradient with an average by sampling from a distribution?

Consider maximizing the function $R(w)$ with parameter $w$ using gradient ascent. However, we don't know the gradient $\nabla_wR(w)$ formula. Now suppose $w$ is sampled from a probability distribution ...
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1answer
815 views

What is the relation between an environment, a state and a model?

In particular, I would like to have a simple definition of "environment" and "state". What are the differences between those two concepts? Also, I would like to know how the concept of model relates ...
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What algorithms are considered reinforcement learning algorithms?

What are the areas/algorithms that belong to reinforcement learning? TD(0), Q-Learning and SARSA are all temporal-difference algorithms, which belong to the reinforcement learning area, but is there ...
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314 views

What is machine learning?

What is the definition of machine learning? What are the advantages of machine learning?
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Where does the hierarchical reinforcement learning framework name “MAXQ” come from?

I've been researching different frameworks for hierarchical RL (mainly options, HAMs, and MAXQ) and noticed that both options and HAMs have names that relate to how they function. I can't seem to find ...
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60 views

What is Federated Learning?

How would you explain Federated Learning in simple layman terms for a non-STEM person? What are the main ideas behind Federated Learning?
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1answer
4k views

What are ontologies in AI?

What exactly are ontologies in AI? How should I write them and why are they important?
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Can CNNs be made robust to tricks where small changes cause misclassification?

I while ago I read that you can make subtle changes to an image that will ensure a good CNN will horribly misclassify the image. I believe the changes must exploit details of the CNN that will be used ...
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1answer
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What is a successor function (in CSPs)?

In Constraint Satisfaction Problems (CSPs), a state is any data structure that supports a successor function, a heuristic function, and a goal test. In this context, what is a successor function?
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1answer
278 views

Is there any difference between ConvNet and CNN?

ConvNet stands for Convolutional Networks and CNN stands for Convolutional Neural Networks. Is there any difference between both? If yes, then what is it? If no, is there any reason behind using ...
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1answer
76 views

What do we mean by 'principal angle between subspaces'?

I came across the term 'principal angle between subspaces' as a tool for comparing objects in images. All material that I found on the internet seems to deal with this idea in a highly mathematical ...
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What is convergence in machine learning?

I came across this answer on Quora, but it was pretty sparse. I'm looking for specific meanings in the context of machine learning, but also mathematical and economic notions of the term in general.
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What is the difference between reinforcement learning and optimal control?

Coming from a process (optimal) control background, I have begun studying the field of deep reinforcement learning. Sutton & Barto (2015) state that particularly important (to the writing of the ...
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What is the relation between the context in contextual bandits and the state in reinforcement learning?

Conceptually, in general, how is the context being handled in contextual bandits (CB), compared to states in reinforcement learning (RL)? Specifically, in RL, we can use a function approximator (e.g. ...
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1answer
106 views

Why do we use the word “kernel” in the expression “Gaussian kernel”?

I've heard the expression "Gaussian kernel" in several contexts (e.g. in the kernel trick used in SVM). A Gaussian kernel usually refers to a Gaussian function (that is, a function similar to the ...
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What are the differences between an agent and a model?

In the context of Artificial Intelligence, sometimes people use the word "agent" and sometimes use the word "model" to refer to the output of the whole "AI-process". For ...
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1answer
82 views

What are the differences between an agent that thinks rationally and an agent that acts rationally?

Stuart Russell and Peter Norvig pointed out 4 four possible goals to pursue in artificial intelligence: systems that think/act humanly/rationally. What are the differences between an agent that ...
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1answer
347 views

Is it standard to say that an evaluation function estimates the “goodness” of a position?

Wikipedia states that: An evaluation function, also known as a heuristic evaluation function or static evaluation function, is a function used by game-playing computer programs to estimate the value ...
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Visualizing the Loss Landscape of Neural Nets: Meaning of the word 'filter'?

I found myself scratching my head when I read the following phrase in the paper Visualizing the Loss Landscape of Neural Nets: To remove this scaling effect, we plot loss functions using filter-wise ...
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1answer
320 views

Are mult-adds and FLOPs equivalent?

I am comparing different CNN architectures for edge implementation. Some papers describing architectures refer to mult-adds, like the MobileNet V1 paper, where it is claimed that this net has 569M ...
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What is the meaning of the words 'bias' and 'variance' in RL?

In reinforcement learning approaches, like temporal-difference (TD) learning or Monte Carlo methods, two of the metrics used to measure their performance are the bias and the variance. What do these ...
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3answers
882 views

What is a high dimensional state in reinforcement learning?

In the DQN paper, it is written that the state-space is high dimensional. I am a little bit confused about this terminology. Suppose my state is a high dimensional vector of length $N$, where $N$ is a ...
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What is the formal terminology for emotion recognition AI?

I'm researching the use of emotion recognition in Intelligent Tutoring Systems and trying to more effectively find and formally reference materials. My question is whether this is the most formal ...
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1answer
150 views

How can I calculate the “mean best fitness” measure in genetic algorithms?

I've just started to learn genetic algorithms and I have found these measurements of runs that I don't understand: MBF: The mean best fitness measure (MBF) is the average of the best fitness values ...
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1answer
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What is asymmetric relaxation backpropagation?

In Chapter 8, section 8.5.2, Raul Rojas describes how the weights for a layer of a neural network can be calculated using a pseudoinverse of the sigmoid function in the nodes, he explains this is an ...
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1answer
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What's the difference between architectures and backbones?

In the paper "ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery", the authors talk about using: Feature Pyramid Networks (as the ...
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1answer
74 views

Aren't scores in the Wasserstein GAN probabilities?

I am quite new to GAN and I am reading about WGAN vs DCGAN. Relating to the Wasserstein GAN (WGAN), I read here Instead of using a discriminator to classify or predict the probability of generated ...
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What is the difference between artificial intelligence and swarm intelligence?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine ...

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