Meta-learning (computer science) (English Wikipedia)

Schmidhuber, Jürgen (2006). "Gödel machines: Fully Self-Referential Optimal Universal Self-Improvers". In B. Goertzel & C. Pennachin, Eds.: Artificial General Intelligence: 199–226.

arxiv.org (Global: 69^th place; English: 59^th place)

Munkhdalai, Tsendsuren; Yu, Hong (2017). "Meta Networks". Proceedings of Machine Learning Research. 70: 2554–2563. arXiv:1703.00837. PMC 6519722. PMID 31106300.
Finn, Chelsea; Abbeel, Pieter; Levine, Sergey (2017). "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks". arXiv:1703.03400 [cs.LG].
Nichol, Alex; Achiam, Joshua; Schulman, John (2018). "On First-Order Meta-Learning Algorithms". arXiv:1803.02999 [cs.LG].
Andrychowicz, Marcin; Denil, Misha; Gomez, Sergio; Hoffmann, Matthew; Pfau, David; Schaul, Tom; Shillingford, Brendan; de Freitas, Nando (2017). "Learning to learn by gradient descent by gradient descent". Proceedings of ICML'17, Sydney, Australia. arXiv:1606.04474.

books.google.com (Global: 3^rd place; English: 3^rd place)

P. E. Utgoff (1986). "Shift of bias for inductive concept learning". In R. Michalski; J. Carbonell; T. Mitchell (eds.). Machine Learning: An Artificial Intelligence Approach. Morgan Kaufmann. pp. 163–190. ISBN 978-0-934613-00-2.

doi.org (Global: 2^nd place; English: 2^nd place)

Schaul, Tom; Schmidhuber, Jürgen (2010). "Metalearning". Scholarpedia. 5 (6): 4650. Bibcode:2010SchpJ...5.4650S. doi:10.4249/scholarpedia.4650.
Lemke, Christiane; Budka, Marcin; Gabrys, Bogdan (2013-07-20). "Metalearning: a survey of trends and technologies". Artificial Intelligence Review. 44 (1): 117–130. doi:10.1007/s10462-013-9406-y. ISSN 0269-2821. PMC 4459543. PMID 26069389.
Brazdil, Pavel; Carrier, Christophe Giraud; Soares, Carlos; Vilalta, Ricardo (2009). Metalearning - Springer. Cognitive Technologies. doi:10.1007/978-3-540-73263-1. ISBN 978-3-540-73262-4.
Gordon, Diana; Desjardins, Marie (1995). "Evaluation and Selection of Biases in Machine Learning" (PDF). Machine Learning. 20 (1–2): 5–22. doi:10.1023/A:1022630017346. Retrieved 27 March 2020.
Schmidhuber, Jürgen; Zhao, J.; Wiering, M. (1997). "Shifting inductive bias with success-story algorithm, adaptive Levin search, and incremental self-improvement". Machine Learning. 28: 105–130. doi:10.1023/a:1007383707642.

googleblog.com (Global: 1,272^nd place; English: 837^th place)

research.googleblog.com

"AutoML for large scale image classification and object detection". Google Research Blog. November 2017. Retrieved 29 March 2018.

harvard.edu (Global: 18^th place; English: 17^th place)

ui.adsabs.harvard.edu

Schaul, Tom; Schmidhuber, Jürgen (2010). "Metalearning". Scholarpedia. 5 (6): 4650. Bibcode:2010SchpJ...5.4650S. doi:10.4249/scholarpedia.4650.

idsia.ch (Global: low place; English: low place)

people.idsia.ch

Schmidhuber, Jürgen (1987). "Evolutionary principles in self-referential learning, or on learning how to learn: the meta-meta-... hook" (PDF). Diploma Thesis, Tech. Univ. Munich.
Schmidhuber, Jürgen (1994). "On learning how to learn learning strategies" (PDF). Technical Report FKI-198-94, Tech. Univ. Munich.

jmlr.org (Global: low place; English: low place)

Zintgraf, Luisa; Schulze, Sebastian; Lu, Cong; Feng, Leo; Igl, Maximilian; Shiarlis, Kyriacos; Gal, Yarin; Hofmann, Katja; Whiteson, Shimon (2021). "VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning". Journal of Machine Learning Research. 22 (289): 1–39. ISSN 1533-7928.

lilianweng.github.io (Global: low place; English: low place)

Weng, Lilian (30 November 2018). "Meta-Learning: Learning to Learn Fast". OpenAI Blog. Retrieved 27 October 2019.

mlr.press (Global: low place; English: low place)

proceedings.mlr.press

Santoro, Adam; Bartunov, Sergey; Wierstra, Daan; Lillicrap, Timothy. "Meta-Learning with Memory-Augmented Neural Networks" (PDF). Google DeepMind. Retrieved 29 October 2019.

neurips.cc (Global: low place; English: low place)

proceedings.neurips.cc

Greenberg, Ido; Mannor, Shie; Chechik, Gal; Meirom, Eli (2023-12-15). "Train Hard, Fight Easy: Robust Meta Reinforcement Learning". Advances in Neural Information Processing Systems. 36: 68276–68299.

nih.gov (Global: 4^th place; English: 4^th place)

ncbi.nlm.nih.gov

Lemke, Christiane; Budka, Marcin; Gabrys, Bogdan (2013-07-20). "Metalearning: a survey of trends and technologies". Artificial Intelligence Review. 44 (1): 117–130. doi:10.1007/s10462-013-9406-y. ISSN 0269-2821. PMC 4459543. PMID 26069389.
Munkhdalai, Tsendsuren; Yu, Hong (2017). "Meta Networks". Proceedings of Machine Learning Research. 70: 2554–2563. arXiv:1703.00837. PMC 6519722. PMID 31106300.

pubmed.ncbi.nlm.nih.gov

Lemke, Christiane; Budka, Marcin; Gabrys, Bogdan (2013-07-20). "Metalearning: a survey of trends and technologies". Artificial Intelligence Review. 44 (1): 117–130. doi:10.1007/s10462-013-9406-y. ISSN 0269-2821. PMC 4459543. PMID 26069389.
Munkhdalai, Tsendsuren; Yu, Hong (2017). "Meta Networks". Proceedings of Machine Learning Research. 70: 2554–2563. arXiv:1703.00837. PMC 6519722. PMID 31106300.

nips.cc (Global: low place; English: 7,050^th place)

papers.nips.cc

Vinyals, O.; Blundell, C.; Lillicrap, T.; Kavukcuoglu, K.; Wierstra, D. (2016). "Matching networks for one shot learning" (PDF). Google DeepMind. Retrieved 3 November 2019.
Snell, J.; Swersky, K.; Zemel, R. S. (2017). "Prototypical networks for few-shot learning" (PDF).

npr.org (Global: 92^nd place; English: 72^nd place)

"Robots Are Now 'Creating New Robots,' Tech Reporter Says". NPR.org. 2018. Retrieved 29 March 2018.

openreview.net (Global: low place; English: low place)

Ravi, Sachin; Larochelle, Hugo (2017). Optimization as a model for few-shot learning. ICLR 2017. Retrieved 3 November 2019.

springer.com (Global: 274^th place; English: 309^th place)

link.springer.com

Gordon, Diana; Desjardins, Marie (1995). "Evaluation and Selection of Biases in Machine Learning" (PDF). Machine Learning. 20 (1–2): 5–22. doi:10.1023/A:1022630017346. Retrieved 27 March 2020.

tennessee.edu (Global: low place; English: 9,008^th place)

trace.tennessee.edu

Begoli, Edmon (May 2014). "Procedural-Reasoning Architecture for Applied Behavior Analysis-based Instructions". Doctoral Dissertations. Knoxville, Tennessee, USA: University of Tennessee, Knoxville: 44–79. Retrieved 14 October 2017.

thecvf.com (Global: low place; English: low place)

openaccess.thecvf.com

Sung, F.; Yang, Y.; Zhang, L.; Xiang, T.; Torr, P. H. S.; Hospedales, T. M. (2018). "Learning to compare: relation network for few-shot learning" (PDF).

toronto.edu (Global: low place; English: 8,821^st place)

cs.toronto.edu

Koch, Gregory; Zemel, Richard; Salakhutdinov, Ruslan (2015). "Siamese Neural Networks for One-shot Image Recognition" (PDF). Toronto, Ontario, Canada: Department of Computer Science, University of Toronto.

worldcat.org (Global: 5^th place; English: 5^th place)

search.worldcat.org

Lemke, Christiane; Budka, Marcin; Gabrys, Bogdan (2013-07-20). "Metalearning: a survey of trends and technologies". Artificial Intelligence Review. 44 (1): 117–130. doi:10.1007/s10462-013-9406-y. ISSN 0269-2821. PMC 4459543. PMID 26069389.
Zintgraf, Luisa; Schulze, Sebastian; Lu, Cong; Feng, Leo; Igl, Maximilian; Shiarlis, Kyriacos; Gal, Yarin; Hofmann, Katja; Whiteson, Shimon (2021). "VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning". Journal of Machine Learning Research. 22 (289): 1–39. ISSN 1533-7928.

Meta-learning (computer science) (English Wikipedia)

abracadoudou.com (Global: low place; English: low place)

bengio.abracadoudou.com

archive.org (Global: 6th place; English: 6th place)

arxiv.org (Global: 69th place; English: 59th place)

books.google.com (Global: 3rd place; English: 3rd place)

doi.org (Global: 2nd place; English: 2nd place)

googleblog.com (Global: 1,272nd place; English: 837th place)

research.googleblog.com

harvard.edu (Global: 18th place; English: 17th place)

ui.adsabs.harvard.edu

idsia.ch (Global: low place; English: low place)

people.idsia.ch

jmlr.org (Global: low place; English: low place)

lilianweng.github.io (Global: low place; English: low place)

mlr.press (Global: low place; English: low place)

proceedings.mlr.press

neurips.cc (Global: low place; English: low place)

proceedings.neurips.cc

nih.gov (Global: 4th place; English: 4th place)

ncbi.nlm.nih.gov

pubmed.ncbi.nlm.nih.gov

nips.cc (Global: low place; English: 7,050th place)

papers.nips.cc

npr.org (Global: 92nd place; English: 72nd place)

openreview.net (Global: low place; English: low place)

springer.com (Global: 274th place; English: 309th place)

link.springer.com

tennessee.edu (Global: low place; English: 9,008th place)

trace.tennessee.edu

thecvf.com (Global: low place; English: low place)

openaccess.thecvf.com

toronto.edu (Global: low place; English: 8,821st place)

cs.toronto.edu

worldcat.org (Global: 5th place; English: 5th place)

search.worldcat.org

archive.org (Global: 6^th place; English: 6^th place)

arxiv.org (Global: 69^th place; English: 59^th place)

books.google.com (Global: 3^rd place; English: 3^rd place)

doi.org (Global: 2^nd place; English: 2^nd place)

googleblog.com (Global: 1,272^nd place; English: 837^th place)

harvard.edu (Global: 18^th place; English: 17^th place)

nih.gov (Global: 4^th place; English: 4^th place)

nips.cc (Global: low place; English: 7,050^th place)

npr.org (Global: 92^nd place; English: 72^nd place)

springer.com (Global: 274^th place; English: 309^th place)

tennessee.edu (Global: low place; English: 9,008^th place)

toronto.edu (Global: low place; English: 8,821^st place)

worldcat.org (Global: 5^th place; English: 5^th place)