Questions tagged [terminology]

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

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Terminology for the use of datasets as data points

As computers are getting bigger better and faster, the concept of what constitutes a single datum is changing. For example, in the world of pen-and-paper, we might take readings of temperature over ...
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2answers
621 views

What is the difference between learning without forgetting and transfer learning?

I would like to incrementally train my model with my current dataset and I asked this question on Github issues, which is what I'm using SSD MobileNet v1: https://github.com/tensorflow/models/issues/...
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99 views

Why do we need learning in unsupervised learning? [duplicate]

I am not clear with the concept that an unsupervised model learns. We are giving an input and output to the supervised model, so that it can generate a particular value, pattern or something out of it ...
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1answer
146 views

What is USV In NLP?

3 SVD Based Methods For this class of methods to find word embeddings (otherwise known as word vectors), we first loop over a massive data set and accumulate word co-occurrence counts in some form of ...
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1answer
83 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 ...
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78 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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3answers
227 views

What is the name of an AI whose primary goal is to create a better AI?

A general AI x creates another AI y which is better than x. y creates an AI better than itself. And so on, with each generation's primary goal to create a better AI. Is there a name for this. By ...
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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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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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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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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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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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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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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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2answers
61 views

What does “immediate vector-valued feedback” mean?

In the book Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning, James Stone says With supervised learning, the response to each input vector is an output ...
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1answer
920 views

What are options in reinforcement learning?

According to a lecture about Reinforcement Learning, the concept of options allows searching the state space of an agent much faster. The lecture came from Nptel [1] (National Program on Technology ...
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1answer
79 views

Biological analogy for boosting and inhibition idea in Hierarchical Temporal Memory (HTM)

I've just watched the 9th episode of HTM school about the "boosting" and "inhibition" ideas. However, I couldn't find the neuroscience counterpart of these terms and concepts. Since HTM is a ...
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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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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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1answer
1k views

What is convergence in machine learning?

I came across this answer on Quora, but it was pretty sparse. I'm looking for specific meanings in the context of machine learning, but also mathematical and economic notions of the term in general.
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385 views

What are the major differences between cost, loss, error, fitness, utility, objective, criterion functions?

I find the terms cost, loss, error, fitness, utility, objective, criterion functions to be interchangeable, but any kind of minor difference explained is appreciated.
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69 views

Is the definition of machine learning by Mitchell in his book “Machine Learning” valid?

The definition machine learning is as follows: A computer program is said to learn from experience E with respect to some task T and performance measure P, if its performance at task T, as ...
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1answer
58 views

Differences between an agent that thinks rationally and an agent that acts rationally?

Stuart Russell and Peter Norvig pointed out 4 four possible goals to pursue in artificial intelligence: systems that think/act humanly/rationally. What are the differences between an agent that ...
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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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69 views

Describing the order of a tensor

When describing tensors of higher order I feel like there is an overloading of the term dimension as it may be used to describe the order of the tensor but also the dimensionality of the... "orders"? ...
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1answer
49 views

What is the prediction accuracy?

In simple words, what is the prediction accuracy? What is it based on? How does it help? When is it used?
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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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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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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 ...
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1answer
61 views

Are CNN, LSTM, GRU and transformer AGI or computational intelligence tools?

Will CNN, LSTM, GRU and transformer be better classified as Computational Intelligence (CI) tools or Artificial General Intelligence (AGI) tools? The term CI arose back when some codes like neural ...
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39 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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59 views

What is the meaning of the words 'bias' and 'variance' in RL?

In algorithms like MC/TD (tabular value approximation) two of the metrics used to measure their performance are the bias and the variance. What do these terms mean? And which characteristic of the ...
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84 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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1answer
50 views

What is “dense” in DensePose?

I've recently come across an amazing work for human pose estimation: DensePose: Dense Human Pose Estimation In The Wild by Facebook. In this work, they have tackled the task of dense human pose ...
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286 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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35 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 ...
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1answer
68 views

Why is Information Filter called Information Filter?

We all know Information Filter is a dual representation of Kalman Filter. The main difference between Information Filter and Kalman Filter is the way the Gaussian belief is represented. In Kalman ...
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1answer
102 views

What is meant by the research topic “Humanitarian AI”?

What exactly is meant by "humanitarian AI"? What research areas does this cover? AI in healthcare? Algorithmic fairness? Applications of AI for economic development? Can anyone provide links to ...
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174 views

What is machine learning?

What is the definition of machine learning? What are the advantages of machine learning?
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1answer
70 views

What does “probabilistically” mean?

I'm reading the A. E. Eiben and J. E. Smith book Introduction to Evolutionary Computing (Springer 2003). On section 3.5 Recombination, page 47, the second paragraph said: Recombination operators ...
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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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87 views

Is there a Hebb neural network?

Is there a Hebb neural network? What kind of functions can it implement? Or, are there multiple "Hebb networks", that is, neural networks that learn in a Hebbian fashion?
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1answer
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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1answer
40 views

Would you term Google's Captchas as Turing Test?

Quoting from Wikipedia page on Turing Test The Turing test, developed by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable ...
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1answer
1k views

What is an agent in Artificial Intelligence?

While studying artificial intelligence, I have often encountered the term "agent" (often autonomous, intelligent). For instance, in fields such as Reinforcement Learning, Multi-Agent Systems, Game ...
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1answer
314 views

What's the difference between a static AI and a dynamic AI?

I recently watched a YouTube video (sorry, can't remember the link) where (a very talented) someone created what they called a "static AI". Somewhere in the video they said something along the lines ...
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1answer
251 views

“Goodness” of a position in an Evaluation Function?

The Wikipedia states that: "An evaluation function, also known as a heuristic evaluation function or static evaluation function, is a function used by game-playing programs to estimate the value or ...
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2answers
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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1answer
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
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 ...