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
1
vote
1answer
55 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 ...
1
vote
1answer
53 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 ...
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 ...
1
vote
2answers
56 views

What is “Word Sense Disambiguation”?

I recently came across this article which cites a paper which apparently won outstanding paper in ACL 2019. The theme is that it solved a longstanding problem called Word Sense Disambiguation. What ...
1
vote
3answers
64 views

Is Superintelligence a function of strength or a category?

Super comes from the Latin and means "above". University of Oxford philosopher Nick Bostrom defines superintelligence as "any intellect that greatly exceeds the cognitive performance of humans in ...
1
vote
1answer
47 views

What is a model and how is it designed?

I read these things on the internet like My model determines the future scope..." or My model gives accurate readings about what the score would be..." What are these models? How are they ...
1
vote
1answer
50 views

What is meant by degrees of freedom of latent variables?

...Designing such a likelihood function is typically challenging; however, we observe that features like spectrogram are effective when latent variables have limited degrees of freedom. This motivates ...
1
vote
1answer
38 views

What are finite horizon look-ahead policies in reinforcement learning?

I was reading the paper How to Combine Tree-Search Methods in Reinforcement Learning published in AAAI Conference 2019. It starts with the sentence Finite-horizon lookahead policies are abundantly ...
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
82 views

What is teacher forcing?

In the paper Neural Programmer-Interpreters, the authors use the teacher forcing technique, but what exactly is it?
1
vote
1answer
46 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
49 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
2answers
184 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 ...
1
vote
1answer
106 views

Is it a valid Deep Neural Network?

For a regression task, I have sequences of training data and if I define the layers of deep neural network to be: Layers=[ sequenceInputLayer(featuredimension) reluLayer dropoutLayer(0.05) ...
1
vote
1answer
34 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 ...
1
vote
1answer
36 views

What is the representational capacity of a learning algorithm? [duplicate]

The definition I see for representational capacity is "the family of functions the learning algorithm can choose from when varying the parameters in order to reduce a training objective." (...
1
vote
1answer
62 views

Who first coined the term “deep learning”?

AFAIK, deep learning became popular in 2012 with the victory of ImageNet Competition - Large Scale Visual Recognition Challenge 2012 where winners of this contest actually used deep learning ...
1
vote
0answers
43 views

Does Algorithmic Mechanism Design come under the field of AI?

I see many papers in AAMAS talk about artificial intelligence and mechanism design simultaneously. I was wondering, for the sake of being pedantic, is mechanism design could be classified under AI.
1
vote
1answer
43 views

What are mono-variable and multi-variable neural networks?

In this document, the terms "Redes Neuronales estáticas monovariables" and "Redes Neuronales estáticas multivariables" are mentioned. What are mono-variable and multi-variable neural networks? Is it ...
1
vote
0answers
18 views

How do CNNs or RNNs “stack the feature of nodes by a specific order”?

I am trying to understand the following statement taken from the paper Graph Neural Networks: A Review of Methods and Applications (2019). Standard neural networks like CNNs and RNNs cannot handle ...
1
vote
1answer
36 views

What is the meaning of “easy negatives” in the context of machine learning?

What does the term "easy negatives" exactly mean in the context of machine learning for a classification problem or any problem in general? From a quick google search, I think it means just negative ...
1
vote
1answer
56 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 ...
1
vote
1answer
29 views

What does “shape information” mean in terms of GAN(generative adversarial networks)?

A paper says However, annotations used as inputs to C-GAN are typically based only on shape information, which can result in undesirable intensity distributions in the resulting artificially-...
1
vote
0answers
28 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 ...
1
vote
0answers
68 views

What is the difference between Knowledge Representation and Automated Reasoning?

Knowledge Representation and Automated Reasoning are two AI subfields which seem to have something to do with reasoning. However, I can't find any information online about their relationship. Are ...
1
vote
1answer
75 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 ...
1
vote
1answer
287 views

How Swarm Intelligence can empower Blockchain?

Are there examples of applications in blockchain consensus using swarm intelligence, as opposed to classical consensus mechanisms like PoW or PBFT? Please note that recent classical consensuses, ...
1
vote
1answer
46 views

What are “function terms” in the context of an ontology?

I was going through the Wikipedia page on ontology components and noticed something that I had been hoping to find, for a long time. In the components' overview it mentioned: Function terms: ...
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 ...
0
votes
1answer
41 views

Is the error function known or unknown?

What is the error function? Is it the same as the cost function? Is the error function known or unknown? When I get the outcome of a neural net I compare it with the target value. The difference ...
0
votes
1answer
60 views

Can neural networks modify their own weights without back-propagation and gradient descent?

Can neural networks modify their own weights without back-propagation and gradient descent?
0
votes
1answer
77 views

What is Cognitive Intelligence?

Similarly to the question, What is artificial intelligence? Cognitive Intelligence, as well as being a part of Artificial Intelligence, is an area that mainly covers the technology and tools that ...
0
votes
1answer
27 views

What are non-held-out data or non-held-out classes?

I'm Spanish and I don't understand the meaning of "non-held-out". I have tried Google Translator and online dictionaries like Longman but I can't find a suitable translation for this term. You can ...
0
votes
0answers
49 views

What are the differences between backbones, frontends, models and architectures in applied deep learning?

Context I'm trying to dive into deep learning for tasks on images, and trying to figure out how to reuse some well-known structures* that have been published, mainly on github. ( *Here, structure can ...
0
votes
0answers
78 views

What is a self-learning model?

Any simple example of a self-learning model (any business use case, banking)? I have found the terms here and here.
0
votes
1answer
33 views

What is the correct name for state explosion from sensor discretization?

The position of a robot on a map contains of an x/y value, for example $position(x=100.23,y=400.78)$. The internal representation of the variable is a 32bit float which is equal to 4 byte in the RAM ...
0
votes
1answer
21 views

Should I call the error “validation error” or “test error” during cross validation?

I'm using 10-fold cross validation on all models. Here you can see both plots: Since I am using k-fold cross validation, is it okay to name it "validation error vs training error" or "test error vs ...

1 2 3
4