Questions tagged [terminology]

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

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33 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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168 views

Why is the target called “target” in Monte Carlo and TD learning if it is not the true target?

I was going through Sutton's book and, using sample-based learning for estimating the expectations, we have this formula $$ \text{new estimate} = \text{old estimate} + \alpha(\text{target} - \text{old ...
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1answer
73 views

What does the notation $\mathcal{N}(z; \mu, \sigma)$ stand for in statistics?

I know that the notation $\mathcal{N}(\mu, \sigma)$ stands for a normal distribution. But I'm reading the book "An Introduction to Variational Autoencoders" and in it, there is this notation:...
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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 ...
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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." (...
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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 ...
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74 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 ...
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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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47 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 ...
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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 ...
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1answer
51 views

How can I classify policy gradient methods in RL?

In the book of Barto and Sutton, there are 3 methods presented that solve an RL problem: DP, Monte Carlo, and TD. But which category does policy gradient methods (or actor-only methods) classify in? ...
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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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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.
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45 views

What does it mean when a model “statistically outperforms” another?

I was reading this paper where they are stating the following: We also use the T-Test to test the significance of GMAN in 1 hour ahead prediction compared to Graph WaveNet. The p-value is less than 0....
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2answers
135 views

What are the main algorithms used in computer vision?

Nowadays, CV has really achieved great performance in many different areas. However, it is not clear what a CV algorithm is. What are some examples of CV algorithms that are commonly used nowadays and ...
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878 views

What is Reinforcement Learning?

What is the cleanest, easiest way to explain someone who is a non-STEM work colleague the concept of Reinforcement Learning? What are the main ideas behind Reinforcement Learning?
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1answer
182 views

How do I recognise a bandit problem?

I'm having difficulty understanding the distinction between a bandit problem and a non-bandit problem. An example of the bandit problem is an agent playing $n$ slot machines with the goal of ...
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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 ...
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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 ...
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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 ...
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62 views

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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1answer
26 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 ...
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2answers
139 views

How can reinforcement learning be unsupervised learning if it uses deep learning?

I was watching a video in my online course where I'm learning about A.I. I am a very beginner in it. At one point in the course, the instructor says that reinforcement learning (RL) needs a deep ...
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2answers
68 views

Are bandits considered an RL approach?

If a research paper uses multi-armed bandits (either in their standard or contextual form) to solve a particular task, can we say that they solved this task using a reinforcement learning approach? Or ...
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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 ...
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1answer
41 views

How is an architecture composed of a second model that validates the first one called in machine learning?

I have a mix of two deep models, as follows: if model A is YES --pass to B--> if model B is YES--> result = YES if model A is NO ---> result = NO So ...
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497 views

Does the “lowest layer” refer to the first or last layer of the neural network?

People sometimes use 1st layer, 2nd layer to refer to a specific layer in a neural net. Is the layer immediately follows the input layer called 1st layer? How about the lowest layer and highest layer?...
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1answer
53 views

What are episodic and non-episodic domains in reinforcement learning?

I was reading about the temporal difference (TD) learning and I read that: TD handles continuing, non-episodic domains Assuming that continuing means non-terminating, what does non-episodic or ...
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2answers
76 views

Is my understanding of the value function, Q function, policy, reward and return correct?

I'm a beginner in the RL field, and I would like to check that my understanding of certain RL concepts. Value function: How good it is to be in a state S following policy π. ...
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74 views

Is the Q value the same as the state-action pair value?

Am I right to say that the Q value of a particular state and action is the same as the state-action pair value of that same state and action?
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135 views

Who first coined the term “artificial general intelligence”?

Similarly to the question Who first coined the term Artificial Intelligence?, who first coined the term "artificial general intelligence"?
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37 views

What is it called in AI when a program is designed to make “x in the style of y”?

Simplified: What is it called in AI when a program is designed to make "x in the style of y;" when it trains off of two types of sources in order to make a thing from source one, informed by features ...
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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 ...
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1answer
54 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 ...
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1answer
139 views

What does “off-the-shelf” mean?

I encountered the phrase/concept off-the-shelf CNN in this paper in which authors used off-the-shelf CNN representation, OverFeat, with simple classifiers to ...
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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 ...
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2answers
108 views

Why is it called back-propagation?

While looking at the mathematics of the back-propagation algorithm for a multi-layer perceptron, I noticed that in order to find the partial derivative of the cost function with respect to a weight (...
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1answer
84 views

What are “proxy data sets” in machine learning?

The paper Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration uses the term "proxy data sets" in this way To develop DL ...
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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-...
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1answer
50 views

What is the type of problem requiring to rate images on a scale?

I'm new to the topic, but I've used some off the shelf knowledge about computer vision for classifying images. For example, you can easily generate labels that can determine whether or not e.g. a ...
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1answer
80 views

What is teacher forcing?

In the paper Neural Programmer-Interpreters, the authors use the teacher forcing technique, but what exactly is it?
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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 ...
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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 ...
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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 ...
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2answers
77 views

What is the name of this neural network architecture with layers that are also connected to non-neighbouring layers?

Consider a feedforward neural network. Suppose you have a layer of inputs, which is feedforward to a hidden layer, and feedforward both the input and hidden layers to an output layer. Is there a name ...
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1answer
454 views

Are model-free and off-policy algorithms the same?

In respect of RL, is model-free and off-policy the same thing, just different terminology? If not, what are the differences? I've read that the policy can be thought of as 'the brain', or decision ...
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84 views

Why are the terms classification and prediction used as synonyms in the context of deep learning?

Why are the terms classification and prediction used as synonyms especially when it comes to deep learning? For example, a CNN predicts the handwritten digit. To me, a prediction is telling the next ...
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1answer
35 views

What is the difference between the concepts “known environment” and “deterministic environment”?

According to the book "Artificial Intelligence: A Modern Approach", "In a known environment, the outcomes (or outcome probabilities if the environment is stochastic) for all actions are given.", and ...
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189 views

What is “Computational Linguistics”?

It's not clear to me whether or not someone whose work aims to improve an NLP system may be called a "Computational Linguist" even when she/he doesn't modify the algorithm directly by coding. Let's ...
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150 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 ...