Concepedia

Few-shot Learning

Few-Shot Learning is a machine learning paradigm within meta-learning and transfer learning that enables models to generalize to new tasks from a minimal number of labeled examples, typically by leveraging prior knowledge acquired from related tasks.

3K

Publications

201.8K

Citations

9.1K

Authors

1.4K

Institutions

Publications per year

2017–2026

3K

Parents

Publications

3K

Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics

DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2023 · 14.2K citations · Full text

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Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Chelsea Finn, Pieter Abbeel, Sergey Levine · arXiv (Cornell University) · 2017 · 5.8K citations · Full text

, , +14

Prototypical Networks for Few-shot Learning

Jake Snell, Kevin Swersky, Richard S. Zemel · arXiv (Cornell University) · 2017 · 5.2K citations · Full text

, , +13

Language Models are Few-Shot Learners

T. B. Brown, Benjamin Mann, Nick Ryder et al. · arXiv (Cornell University) · 2020 · 3K citations · Full text

, , +13

Optimization as a Model for Few-Shot Learning

Sachin Ravi, Hugo Larochelle · International Conference on Learning Representations · 2017 · 2.4K citations

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1–5 of 3K

Authors

9.1K

  1. YY
    Yi Yang

    University of Technology Sydney, Australia

    19 publications · 1.4K citations

    17

    h-index

  2. GL
    Guosheng Lin

    Nanyang Technological University, Singapore

    19 publications · 2.8K citations

    17

    h-index

  3. TD
    Trevor Darrell

    University of California, Berkeley, United States

    20 publications · 4.1K citations

    17

    h-index

  4. LZ
    Luke Zettlemoyer

    University of Washington, United States

    15 publications · 1.7K citations

    14

    h-index

  5. JH
    Junwei Han

    Northwestern Polytechnical University, China

    14 publications · 1.6K citations

    14

    h-index

1–5 of 9.1K

Institutions

1.4K

  1. Chinese Academy of Sciences

    Beijing, China

    39 h-index

    298 publications

    13.4K citations

  2. Tsinghua University

    Beijing, China

    37 h-index

    217 publications

    22K citations

  3. Nanyang Technological University

    Singapore, Singapore

    37 h-index

    144 publications

    14.8K citations

  4. Google (United States)

    Mountain View, United States

    36 h-index

    173 publications

    15.2K citations

  5. University of Chinese Academy of Sciences

    Beijing, China

    36 h-index

    262 publications

    11.3K citations

  6. Northwestern Polytechnical University

    Xi'an, China

    30 h-index

    164 publications

    12.7K citations

  7. Zhejiang University

    Hangzhou, China

    29 h-index

    144 publications

    6.4K citations

  8. Peking University

    Beijing, China

    28 h-index

    100 publications

    7.4K citations

1–8 of 1.4K

Venues

  1. arXiv (Cornell University)

    Repository · 553 publications · 47.2K citations

    84

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 89 publications · 5.3K citations

    43

    h-index

  3. 36

    h-index

  4. 32

    h-index

  5. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 43 publications · 3.5K citations

    30

    h-index

1–5