Editing Self-Supervised Learning (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Self-supervised learning''' — A form of unsupervised learning where supervision signals are generated automatically from the data, without human annotation.
* '''Pretext task''' — An artificially constructed task whose labels are derived from the data itself, designed to force the model to learn useful representations.
* '''Masked language modeling (MLM)''' — A pretext task where random tokens in a sequence are masked and the model must predict them. Used to train BERT.
* '''Next sentence prediction''' — A pretext task where the model predicts whether two sentences are consecutive or randomly paired.
* '''Contrastive learning''' — An SSL approach where the model learns by contrasting similar (positive) and dissimilar (negative) pairs of examples.
* '''Positive pair''' — Two views or augmentations of the same data point that should be represented similarly.
* '''Negative pair''' — Two different data points whose representations should be pushed apart.
* '''Augmentation''' — Transformations applied to data (cropping, color jitter, masking) to create different views of the same underlying content.
* '''Representation''' — A dense vector capturing the semantically meaningful content of a data point, learned without supervision.
* '''Downstream task''' — The actual task of interest (classification, detection, etc.) for which the self-supervised representation is subsequently used.
* '''Linear probing''' — Evaluating SSL representations by training only a linear classifier on frozen features; measures representation quality.
* '''SimCLR''' — A simple contrastive learning framework for visual representations (Google, 2020).
* '''BYOL (Bootstrap Your Own Latent)''' — A contrastive SSL method that does not use negative samples; uses a momentum encoder.
* '''MAE (Masked Autoencoder)''' — An SSL approach for vision that masks large portions of image patches and reconstructs them; analogous to BERT for images.
* '''DINO''' — A self-supervised vision transformer method using self-distillation without labels.
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