# Domain Adaptation and Few-Shot Learning

{
  "id": "T11307",
  "title": "Domain Adaptation and Few-Shot Learning",
  "url": "/topics/T11307",
  "kind": "topic-directory",
  "aeo_cohort": "topic-directory",
  "provider": "openalex",
  "revision": "ac259e43082f99b9",
  "catalogue_revision": "f050b5d4780b1289",
  "numeric_address": "36183004611249371",
  "address_version": "morton4x16-v1",
  "coordinates": [
    3,
    17,
    1702,
    11307
  ],
  "answer_status": "Directory metadata; local answer requires separate source review",
  "truth_status": "Subject descriptor, not a factual answer or a demonstrated knowledge gap"
}

This cluster of papers focuses on the advances in transfer learning and domain adaptation, including topics such as few-shot learning, unsupervised learning, representation learning, deep networks, meta-learning, visual recognition, semi-supervised learning, and clustering analysis.

Directory metadata is not a factual answer or evidence of a global knowledge gap.

Source: https://openalex.org/T11307

No owner-reviewed local answer yet.