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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 does it mean to "learn a distribution", and what does it contain?

When I was reading about discriminative vs generative models, I came across their definitions: Given a distribution of inputs $X$ and labels $Y:$ Discriminative models learn the conditional ...
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2 answers
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What is an "inference kernel"?

In the recent event where ChatGPT "went crazy", this term was used in the official post-mortem to describe what happened: In this case, the bug was in the step where the model chooses these ...
hippietrail's user avatar
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1 answer
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What constitutes a 'backdoor' attack in machine learning models?

I've recently come across the term "backdoor attack" in the context of machine learning and I'm trying to understand its precise definition and characteristics. From what I gather, backdoor ...
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What does it mean if I trained my model with more steps per epoch than the total number of training images I have?

I'm having a little bit of trouble understanding what steps per epoch really means. I've read that Number of Steps per Epoch = (Total Number of Training Samples) / (Batch Size), however I don't ...
Triana Anderson's user avatar
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What is the name of this construction for a compound policy that operates over distinct action sets?

I am developing an RL algorithm with a policy that needs to compute valid probabilities over multiple distinct action sets. I think I have a construction that will work, but I do not know what it is ...
Wowee's user avatar
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1 answer
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Are the Dot Product and Tensor Product the same thing in Machine Learning?

I'm currently reading "Deep Learning with Python, Second Edition" by François Chollet, and I need help understanding one thing. Below paragraph was copied from the page 41 2.2.3 Tensor ...
Kamil Bęben's user avatar
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5 answers
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Do full-text translators such as DeepL or Google Translate fall under the term "Generative AI"?

My question relates to full-text translators that are not specifically based on LLMs. My current understanding is that the term Generative AI goes beyond LLMs and that the full-text translators (...
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In the paper "LLM in a flash," what is meant by an up projection or down projection layer?

In the paper, they first use the terms "up projection layer," and similarly for down projection, in this paragraph in the introduction: Row-column bundling: We store a concatenated row and ...
Tyler's user avatar
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Is there a standard nomenclature for model names suffixed by strings such as "Q4_K_S"?

Many models specify details using prefixes such as Q6_K or Q4_K_S. It seems obvious that the ...
Mark Harrison's user avatar
2 votes
2 answers
243 views

Would a pipeline of different models be considered Ensemble Learning?

For example, if I have a problem in which I try to predict if it is a nice day for jogging from a corpus of images, I might first convert the images to text descriptions (ex. raining in forrest, ...
user3517818's user avatar
4 votes
3 answers
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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?
user946822's user avatar
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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 ...
Tarique's user avatar
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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 ...
JJJohn's user avatar
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3 votes
1 answer
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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 ...
Vladislav Gladkikh's user avatar
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2 answers
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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 "...
Geremia's user avatar
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2 answers
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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 ...
Robin van Hoorn's user avatar
1 vote
2 answers
80 views

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 ...
stkuser's user avatar
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2 answers
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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 ...
Mew's user avatar
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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 ...
Rubén's user avatar
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1 answer
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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, ...
AlphaBit95's user avatar
1 vote
1 answer
181 views

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 ...
Rhee's user avatar
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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 ...
Sam's user avatar
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1 answer
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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 ...
SomeoneUnknown's user avatar
-1 votes
1 answer
353 views

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 ...
AAA's user avatar
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1 answer
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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. $$\...
Jaume Oliver Lafont's user avatar
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2 answers
2k views

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 ...
Saptam's user avatar
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1 answer
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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" ...
aletelecomm's user avatar
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1 answer
262 views

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 ...
DerOeko's user avatar
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2 votes
1 answer
227 views

Exact definition of WRN-d-k (Wide ResNet)

I am a little confused about the WRN-d-k notation from Wide Residual Networks. To quote the paper, In the rest of the paper we use the following notation: WRN-n-k denotes a residual network that has ...
nalzok's user avatar
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6 votes
1 answer
4k views

Is large language model and foundation model the same thing?

I read a lot about foundation model and large language model. However, I dont find a clear definition what exactly is a foundation model. Is large language model and foundation model the same thing?
Exploring's user avatar
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2 answers
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What is the relationship between data science, artificial intelligence,machine learning and computer vision?

I am beginner to this field and i am trying to find big picture and i have tried to explore youtube and google images in this regard. According to my understanding ,machine learning is subset of ...
DSP_CS's user avatar
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4 votes
2 answers
2k views

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?
aliiiiiiiiiiiiiiiiiiiii's user avatar
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1 answer
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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 ...
hanugm's user avatar
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What is single object localization?

Object detection is said to be combination of object localization and image classification. However, when reviewing localization, I often come across the term "single-object" localization, ...
akastack's user avatar
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1 answer
77 views

Where does the "rectified" in ReLU come from?

ReLU stands for Rectified Linear Unit. Linear Unit, I understand, since the function is piecewise linear. But what does rectified mean? I looked up the definition and it said: denoting an electric ...
a6623's user avatar
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1 vote
0 answers
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Is there a name for this model?

I have an image autoencoder model trained as follows: Step 1) train a GAN to obtain a generator capable of drawing from the data manifold by sampling a normal distribution in latent space Step 2) ...
user11305730's user avatar
1 vote
0 answers
91 views

Is item-based collaborative filtering the same thing as content-based filtering?

According to this Google dev page content-based filtering Uses similarity between items to recommend items similar to what the user likes. collaborative filtering Uses similarities between queries ...
s1234567a's user avatar
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1 answer
190 views

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 ...
rp2001's user avatar
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1 vote
0 answers
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What are semantic word spaces in NLP?

In the abstract of this paper, it's written Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. I would like to understand what semantic ...
Hermi's user avatar
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1 answer
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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 "...
Trong-Thang Pham's user avatar
1 vote
2 answers
62 views

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-...
hanugm's user avatar
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0 votes
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Is the "Helvetica scenario" mentioned here related to Artificial Intelligence?

Consider the following sentence from the original GAN paper titled Generative Adversarial Nets in particular, $G$ must not be trained too much without updating $D$, in order to avoid "the ...
hanugm's user avatar
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2 votes
2 answers
4k views

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 ...
user0193's user avatar
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1 vote
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What do "large variables" and "small weights" mean in these sentences?

I'm trying to understand these two points from an article: Models with large variables i.e weight matrices. As a consequence such models have correspondingly large gradients and optimizer states. The ...
NRain's user avatar
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2 votes
1 answer
338 views

What is a 'degenerate run' in evaluating model performance?

I've recently come across a paper that uses the term "degenerate run", but I'm not sure if I understand what it means. The idea is that when they report the average performance of running ...
Pedram's user avatar
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1 vote
0 answers
125 views

What does "position" in "each position in the decoder" denote in the Transformer's original paper?

I am reading Attention is All You Need and I feel confused about the word "position" in this paper, by the way I'm not native English speaker which may cause my confusion which has confused ...
zenga's user avatar
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2 votes
1 answer
146 views

How to construct a reward function for a "wait and see" problem

I'm working on a problem that I think could probably be represented as a reinforcement learning task, but I'm uncertain about how to design the reward function. The core task is essentially a ...
user336650's user avatar
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0 answers
419 views

Which algorithm can find the best combination of players to maximize the chance of getting a high score?

I am looking for the right terminology for this problem, so I know what to learn about. Imagine a population of 100 people in a town. The town has a sport team with 10 positions that play in ...
vtscop's user avatar
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5 votes
1 answer
250 views

Does the term "data augmentation" imply increasing the training dataset?

I have a manuscript that has been reviewed and one of the reviewers commented on my use of the term " data augmentation", saying that it might not be the appropriate term in my case (...
Benjamin Cretois's user avatar
1 vote
1 answer
58 views

Should I need to interpret the word "metric" in "performance metric" rigorously?

Consider the following abstract from the research paper titled A Note on the Inception Score for instance Deep generative models are powerful tools that have produced impressive results in recent ...
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