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Questions tagged [terminology]

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

46 questions with no upvoted or accepted answers
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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 ...
4
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0answers
30 views

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 ...
4
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0answers
48 views

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 ...
4
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0answers
93 views

$\frac{P(x_1 \mid y, s = 1) \dots P(x_n \mid y, s = 1) P(y \mid s = 1)}{P(x \mid s = 1)}$ 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: ...
4
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1answer
172 views

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 ...
3
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1answer
107 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 ...
3
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1answer
88 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 ...
3
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0answers
100 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 ...
3
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0answers
115 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-...
3
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1answer
89 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 ...
2
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0answers
17 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-...
2
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0answers
37 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-...
2
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0answers
18 views

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 ...
2
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0answers
20 views

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 ...
2
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0answers
26 views

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 ...
2
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0answers
30 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 ...
2
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0answers
49 views

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 ...
2
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0answers
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 ...
2
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0answers
418 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 ...
2
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0answers
43 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 ...
2
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0answers
91 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 ...
2
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0answers
455 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 ...
2
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0answers
38 views

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 ...
2
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0answers
331 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
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0answers
11 views

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 ...
1
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0answers
24 views

Do literature uses (text) encoding and (word) embedding in a loose sense?

Many research papers use the word "encoding" in many ways. One way is that they use the word "encoding" for models that do convert the text into a vector (say text encoding). But, &...
1
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0answers
14 views

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 "$...
1
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0answers
159 views

What is MNLI-(m/mm)?

I came across the term MNLI-(m/mm) in Table 1 of the paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. I know what MNLI stands for, i.e. Multi-Genre Natural ...
1
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0answers
47 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 ...
1
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1answer
524 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
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1answer
86 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 ...
1
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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
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1answer
90 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
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1answer
35 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
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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
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0answers
87 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
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1answer
53 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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0answers
18 views

What is the difference between the definition of “accuracy” in machine learning and federated learning?

What is the difference between the definition of "accuracy" in machine learning and federated learning? In particular, how is the accuracy calculated in the following paper? Cai, Lingshuang,...
0
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0answers
17 views

When a deep learning paper mentions projections does that mean no bias?

Sometimes a paper mentions a projection layer where some dimensionality is projected onto another to enforce some downstream dimensionality matching requirement. I actually don't have any links at ...
0
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1answer
52 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_{...
0
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0answers
8 views

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 ...
0
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0answers
57 views

Is my reward function non-Markovian?

I am working on an RL problem where the time when the agent obtains the reward for taking action $a$ in time step $t$ is stochastic. In fact, there is no immediate reward for taking action $a$ in time ...
0
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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 ...
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0answers
233 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
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1answer
91 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 ...
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0answers
21 views

Why Word2Vec is called a neural model if no neural network is used in it?

Word2Vec model does not use any neural network. It uses logistic regression only. Consider the following paragraph from p:18 of Vector Semantics and Embeddings We’ll see how to do neural ...