Linked Questions
17 questions linked to/from What is self-supervised learning in machine learning?
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What is the relation between semi-supervised and self-supervised visual representation learning?
What's the differences between semi-supervised learning and self-supervised visual representation learning, and how they are connected?
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How does the (decoder-only) transformer architecture work?
How does the (decoder-only) transformer architecture work which is used in impressive models such as GPT-4?
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Which tasks are called as downstream tasks?
The following paragraph is from page no 331 of the textbook Natural Language Processing by Jacob Eisenstein. It mentions about certain type of tasks called as downstream tasks. But, it provide no ...
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What is the difference between self-supervised and unsupervised learning?
What is the difference between self-supervised and unsupervised learning? The terms logically overlap (and maybe self-supervised learning is a subset of unsupervised learning?), but I cannot pinpoint ...
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Do GANs come under supervised learning or unsupervised learning?
Do GANs come under supervised learning or unsupervised learning?
My guess is that they come under supervised learning, as we have labeled dataset of images, but I am not sure as there might be other ...
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How to generate labels for self-supervised training?
I've been reading a lot lately about self-supervised learning and I didn't understand very well how to generate the desired label for a given image.
Let's say that I have an image classification task, ...
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How to understand the concept of self-supervised learning in AI?
I am new to self-supervised learning and it all seems a little magical at the moment.
The only way I can get an intuitive understanding is to assume that, for real-world problems, features are still ...
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Where do the feature extraction and representation learning differ?
Feature selection is a process of selecting a subset of features that contribute the most.
Feature extraction allows getting new features that are not actually present in the given set of features.
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What is the purpose of the GAN?
The Generative Adversarial Network (GAN) is composed of a generator $G$ and a discriminator $D$. How do these two components interact? What is the intuition behind the GAN, its purpose, and how it is ...
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How Does AlphaGo Zero Implement Reinforcement Learning?
AlphaGo Zero (https://deepmind.com/blog/alphago-zero-learning-scratch/) has several key components that contribute to it's success:
A Monte Carlo Tree Search Algorithm that allows it to better search ...
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What is the difference between distant supervision and self-supervision?
Weak supervision is supervised learning, with uncertainty in the labeling, e.g. due to automatic labeling or because non-experts labelled the data [1].
Distant supervision [2, 3] is a type of weak ...
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Is it possible to pre-train a CNN in a self-supervised way so that it can later be used to solve an instance segmentation task?
I would like to use self-supervised learning (SSL) to learn features from images (the dataset consists of similar images with small differences), then use the resulting trained model to bootstrap an ...
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Does self-supervised learning require auxiliary tasks?
Self-supervised learning algorithms provide labels automatically. But, it is not clear what else is required for an algorithm to fall under the category "self-supervised":
Some say, self-...
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What is the relation between self-taught learning and transfer learning?
I am new to transfer learning and I start by reading A Survey on Transfer Learning, and it stated the following:
according to different situations of labeled and unlabeled data in the source domain, ...
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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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