Questions tagged [terminology]
For questions related to the definition of and use of terminology in the context of Artificial Intelligence
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What is meant by "well-behaved gradient" in this context?
Consider the following statement (from the paper Generative Adversarial Nets) about the success of discriminative models
So far, the most striking successes in deep learning have involved ...
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What should be taken as random variables in the distributions of datasets?
Consider the following two paragraphs taken from the paper titles Generative Adversarial Nets by Ian J. Goodfellow et.al
#1: Abstract
We propose a new framework for estimating generative models via ...
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What is a pipeline in machine learning?
I have heard the term "pipeline" used in many different contexts. Now I'm trying to bring some clarity to the terminology: What exactly is a "pipeline" in machine learning?
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Does it classify as Machine Learning?
I have a gaussian distributed time series ($X_t$) with some parameters in my experiment. Suppose I want to know the mean $\mu$. If I define another time series $Y_t$ such that $Y_t=X_t-a$ for all $t$. ...
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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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Why is it called multi-headed attention?
Why do we call the attention layer in transformers multi-headed attention when in practice all the attention matrices from different heads (W,K,V) for a single layer are concatenated to perform the ...
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In the context of lenet, does C1 refer to the conv layer or the output of the conv layer?
I'm studying lenet.
C1 is the layer
According to a tutorial, C1 is
the first convolutional layer with 6 convolution kernels of size 5× 5.
C1 is the feature map
However, I believe that the part ...
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What do we mean by "orderly opinions" in this sentence in the context of Bayes theorem?
In this page, it's written (emphasis mine)
If probabilities are thought to describe orderly opinions, Bayes theorem describes how the opinions should be updated in the light of new information
What ...
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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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Why there are only three machine learning paradigms: supervised, unsupervised, reinforcement?
I read in books, blogs, and articles that there are three learning paradigms: supervised, unsupervised, and reinforcement.
However, I have never found a proof that this list is exhaustive. Can it be ...
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Are Cellular Neural Networks one type of Neural Networks?
I am researching Cellular Neural Networks and have already read Chua's two articles (1988). In cellular neural networks, a cell is only in relation with its neighbors. So it is easy to use them for ...
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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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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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Is the traditional meaning of "strong AI" outmoded?
Traditionally, "strong AI" refers to Artificial General Intelligence, the human mind understood as an algorithm (Searle, Chinese Room) and Artificial Consciousness.
But recent advances in Artificial ...
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What is the difference between a performance standard and performance measure?
I am reading AI: A Modern Approach. In the 2nd chapter when introducing different agent types, i.e., reflex, utility-based, goal-based, and learning agents, I understood that all types of agents, ...
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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 ...
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What is local consistency in constraint satisfaction problems?
In the Constraint Propagation in CSP, it is often stated that pre-processing can solve the whole problem, so no search is required at all. And the key idea is local consistency. What does this ...
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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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What is the difference between actor-critic and advantage actor-critic?
I'm struggling to understand the difference between actor-critic and advantage actor-critic.
At least, I know they are different from asynchronous advantage actor-critic (A3C), as A3C adds an ...
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What is a beam?
For example, faster-whisper's transcribe function takes an argument
beam_size: Beam size to use for decoding.
What does "...
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What is the difference between representation and embedding?
As I searched about this two terms, I found they are somehow like each other, both try to create a vector from raw data as I understood. But, what is the difference of this two term?
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Origins of the name of convolutional neural networks
Convolutional neural networks (CNNs) contain convolutional layers. In modern deep learning libraries such as Tensorflow and PyTorch, convolutional layers are implemented by using the cross-correlation ...
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What is the difference between an observation and a state in reinforcement learning?
I'm studying reinforcement learning. It seems that "state" and "observation" mean exactly the same thing. They both capture the current state of the game.
Is there a difference between the two terms?...
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What is the "temperature" in the GPT models?
What does the temperature parameter mean when talking about the GPT models?
I know that a higher temperature value means more randomness, but I want to know how randomness is introduced.
Does ...
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Are the held-out datasets used for testing, validation or both?
I came across a new term "held-out corpora" and I confused regarding its usage in the NLP domain
Consider the following three paragraphs from N-gram Language Models
#1: held-out corpora as a ...
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What does 'channel' mean in the case of an 1D convolution?
While reading about 1D-convolutions in PyTorch, I encountered the concept of channels.
...
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What is curriculum learning in reinforcement learning?
I recently came across the term "curriculum learning" in the context of DRL and was intrigued by its potential to improve the learning process. As such, what is curriculum learning? And how ...
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Term for algorithms that are not trained
Before the advent of neural architectures, many AI domains (e.g. speech recognition and computer vision) used algorithms that consisted of a series of hand-crafted transformations for feature ...
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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 ...
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Is manual binding output to input also an AI?
I know AI is primarly training a machine by samples of input-output in order it would learn itself about relations between the input and the output.
What if I manually add the relations? Is that still ...
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What is the difference between features and inputs in machine learning?
I have seen many places that features and inputs have been used interchangeably when talking about machine learning especially deep neural networks. I want to know if they are indeed the same thing or ...
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What is meant by "spatial encoding" in the context of convolutional neural networks?
Consider the following excerpt from the abstract of the research paper titled Squeeze-and-Excitation networks by Jie Hu et al.
Convolutional neural networks are built upon the convolution operation, ...
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What is artificial intelligence?
What is the definition of artificial intelligence?
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What is a "canonical space"?
I am reading the paper on 3D reconstruction, ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction, and I encountered the term "canonical space".
What is a "...
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Are "prompt engineering" and "prompt design" used as synonymous?
Are "prompt engineering" and "prompt design" used as synonymous / equivalent terms on the day to day communications (not research papers) in Artificial Intelligence community ? Do ...
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When is it necessary to explicitly define both the state and observation space in a custom environment?
I'm fairly new to reinforcement learning concepts, and I'm trying to implement a simple custom environment. In my custom environment, I have a scenario where I have multiple continuous state spaces, ...
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What is the difference between the term "generative" in classical machine learning and deep learning?
There are lots of explanations on DGM (Deep Generative Model) and generative classifier (most of the explanations on which are about generative classifier vs discriminative classifier)
But, I can ...
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Do the terms 'sample complexity' and 'sample efficiency' mean the same thing in RL context
For example, the the paper Soft Actor-Critic:Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, both terms are mentioned but without explaining. I have seen them in other ...
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Is my understanding correct regarding the difference between policy and plan?
I am confused regarding the difference between policy and plan in reinforcement learning. According to my understanding, when we calculate the value of state using Bellman equation in deterministic ...
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Why could there be "information leak" if we do not use fixed horizons?
In this page Limitations on horizon length from the Imitation library, the authors recommend that the user sticks to fixed horizon experiments because there could be "information leak" ...
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Sutton & Barto: what are parametrized functions?
From "Reinforcement Learning: An introduction (2nd ed.)" by Richard S. Sutton and Andrew G. Barto, on page 59
Instead, the agent would have to maintain $v_\pi$ and $q_\pi$ as parameterized ...
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What is the name of a feature space which has consistant distance-related properties?
What is the word describing a feature space where distance between two elements has a decisive informational value, whatever the pair of elements is?
For example if a model creates embeddings for ...
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Does this property in product fuzzy logic have a name and any consequences?
In product fuzzy logic, the $AND$ operator of two variables $x_0$ and $x_1$ is the product $x_0x_1$.
Using the $NOT(x)$ as $1-x$, expressions for the other three minterms are easily obtained.
$$\...
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What is the definition of a continuous state/action space?
This question is a result of a discussion with one of my more math-minded friends. When I accidentally mentioned the term continuous state space, he corrected me by saying that I am most probably ...
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What are all the possible usages of 'multilayer perceptron'?
The term 'multilayer perceptron' has been used in literature in various ways in the literature.
I am presenting some of them below
As a feed-forward neural network [1].
As a fully connected feed-...
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What exactly is the AI explainability problem?
I am pretty new to AI and have recently been paying attention to AI explainability and the fact that it remains a hurdle within the path of commercializing certain AI systems in health for instance. I ...
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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 ...
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What are the differences between a knowledge base and a knowledge graph?
During my readings, I have seen many authors using the two terms interchangeably, i.e. as if they refer to the same thing. However, we all know about Google's first quotation of "knowledge graph&...
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Is REINFORCE the same as 'vanilla policy gradient'?
I don't know what people mean by 'vanilla policy gradient', but what comes to mind is REINFORCE, which is the simplest policy gradient algorithm I can think of. Is this an accurate statement?
By ...
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Confusion about bias in McCulloch-Pitts neurons
I just have a quick question, maybe I am too nit picky here.
We recently had an introductory lecture to AI in university and the professor talked about McCulloch-Pitts neurons, e.g. activation as soon ...