Questions tagged [terminology]

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

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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 among others, convolutional layers are implemented by using the ...
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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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$\frac{P(x_1 \mid y, s = 1) \dots P(x_n \mid y, s = 1) P(y \mid s = 1)}{P(x \mid s = 1)}$ indicates that naive Bayes learners are global learners?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3. Learning under sample selection bias, the author says the following: ...
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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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113 views

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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130 views

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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108 views

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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126 views

What are the differences between learning by analogy, inductive learning and explanation based learning?

I have heard of the concepts of learning by analogy (which is quite self-explanatory), inductive learning and explanation-based learning. I tried to learn about inductive learning and explanation-...
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95 views

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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34 views

What is the difference between “AI Methods” and “AI Techniques”?

These are words that we frequently come upon. What can be said about the differences? Would these two words' subheadings be different?
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61 views

What does 'channel' mean in the case of an 1D convolution?

While reading about 1D-convolution in PyTorch, I encountered the concept of channels ...
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24 views

What is meant by Hinton when he refers to "Part-Whole Hierarchies" in his GLOM framework

I was recently reading Hinton's GLOM idea How to represent part-whole hierarchies in a neural network, and I am simply unsure about what exactly he means when he says parsing images into "part-...
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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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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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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 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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32 views

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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914 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 meant by "arranging the final features of CNN in a grid" and how to do it?

In the paper What You Get Is What You See: A Visual Markup Decompiler, the authors have proposed a method to extract the features from the CNN and then arrange those extracted features in a grid to ...
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21 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 ...
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44 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 ...
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92 views

How does Friend-or-Foe Q-learning intuitively work?

I read about Q-Learning and was reading about multi-agent environments. I tried to read the paper Friend-or-Foe Q-learning, but could not understand anything, except for a very vague idea. What does ...
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528 views

What are the differences between Deepfakes, FaceSwap and Face2Face?

I've compared videos manipulated with three different automated face manipulation methods: Deepfakes, Face2Face, and FaceSwap. Surprisingly, I found the output videos quite different: Deepfakes and ...
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Continuous-attractor neural network explanation

I am reading about CANN, however, I do not seem to grasp what it is. Maybe someone who has worked with it can explain it? I found out about it while reading about RatSLAM. I understand that it helps ...
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334 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, ...
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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 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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Why actual mapping is called as unreferenced mapping in this context of residual framework?

Consider the following statements from the research paper titled Deep Residual Learning for Image Recognition by Kaiming He et al. #1: We explicitly reformulate the layers as learning residual ...
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Is there any difference between "image generation" and "image synthesis"?

Generative Adversarial networks (aka GANs) are used for image generation. The phrase image synthesis is also used in literature. I know that the phrase image generation stands for An act of ...
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11 views

What is language-conditioned visual reasoning?

Can anyone explain what language-conditioned visual reasoning is? I saw this term in this paper and I searched on the internet but I couldn't find a proper explanation.
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23 views

Is label-embedding similar to one-hot encoding?

In one-hot encoding, a vector is given to each class label. For each class, only one entry of the vector is equal to 1 and the remaining entries are zeros in this encoding. Thus, in one-hot encoding, ...
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31 views

Do the terms multi-task and multi-output refer to the same thing in the context of deep learning?

Do the terms multi-task and multi-output refer to the same thing in the context of deep learning (with neural networks)? For example, do neural networks for multi-task learning use multiple outputs? ...
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What is meant by "Zero-Shot Visual Recognition"?

Many recent research papers contain the phrase "Zero-Shot Visual Recognition". What exactly is meant by zero-shot visual recognition? Does the task need only images or also the other data ...
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What do "spatial" and "temporal" mean in the context of image processing?

I am new to image processing. I am trying to understand CNNs from this blog post. Here's an excerpt from that article that mentions these terms. A ConvNet is able to successfully capture the Spatial ...
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What's mutual exclusivity in meta-learning?

What do we mean by mutual exclusivity of tasks? This work (E Pan, 21) and this one (M Yin, 20) state that most classification meta-learning algorithms fail for non-mutually exclusive tasks as the ...
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Terminology for the weight of likelihood ratio/score function?

If we estimate the gradient of $f(x)$ using the likelihood ratio/score function, i.e. $$\nabla f = f^*\dfrac{\partial \log p(x)}{\partial \theta}$$ is there any agreed upon terminology to call "$...
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49 views

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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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.
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125 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 ...
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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-...
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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 ...
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114 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 ...
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59 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: ...
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When can we call a feature "hierarchial"?

Features in machine learning are the attributes of the elements of a data set. They are considered as random variables in probability. Consider the following excerpt from 1.1: The deep learning ...
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What does it mean by "low-level" and "high-level" in features generated by CNN?

Across the literature, the terms "high-level" and "low-level" are generally used as an adjective to the features generated by the convolution neural network. Should I understand ...
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49 views

What are the different possible usages of the word "i.i.d" in machine learning?

The acronym "iid" stands for "independent and identically distributed". It is a property of a sequence of random variables. You can read here for more details. This question is ...
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Can I always use "encoding" and "embedding" interchangeably?

This question is restricted to text domain only. The meaning of word "encode" is Convert (information or an instruction) into a particular form. One which performs encoding is called encoder....
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What is meant by domain in the notations of geometric deep learning?

While reading the Notation of the paper titled Geometric Deep Learning Grids, Groups, Graphs, Geodesics, and Gauges, I came across the following notations. $$ \...
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Is there a term for performance metric like prediction time on a new/unseen example?

The performance entry on Google's machine-learning glossary doesn't mention prediction time on a new/unseen example which is important for production use. Is there a term to refer to that metric?
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Why is the activation function "HardShrink" called so?

Neural networks contain activation functions, which are responsible for the non-linearity of their intermediate and final outputs. Hardshrink is the name of an activation function, which is defined ...