ConceptRepresentation Learning
Representation Learning
A subfield of machine learning that enables models to automatically learn to transform raw data into high-dimensional feature vectors, such that similar samples are positioned closer together in the feature space. It is considered a core concept underlying deep learning.
Timeline (last 90 days)
Oct 6
The basic idea of embedding vectors is to map high-dimensional, discrete, or hard-to-compute objects into low-dimensional continuous dense vectors, so that semantically or visually similar objects are closer in vector space.
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