Transcription of Self-Prediction and Contrastive Learning
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Self-Prediction and Contrastive Learning
Self-Supervised LearningSelf-Prediction and Contrastive LearningLilian Weng, Jong Wook KimNeurIPS 2021 Tutorial Introduction: motivation, basic concepts, examples. Early work: look into connection with old methods. Methods Self-Prediction Contrastive Learning Pretext tasks: a wide range of literature review. Techniques: improve training efficiency. Future directionsOutline2 IntroductionWhat is self-supervised Learning and why we need it?3 Self-Supervised Learning (SSL) is a special type of representation Learning that enables Learning good data representation from unlabelled is motivated by the idea of constructing supervised Learning tasks out of unsupervised is Self-Supervised Learning ?
The part to be predicted pretends to be missing.Methods for Framing Self-Supervised Learning Tasks? “Intra-sample” prediction 19. Contrastive learning: Given multiple data samples, the task is to predict the ... Order of image patches (e.g., relative position, jigsaw puzzle) Image rotation Counting features across patches
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