Talk:Sample complexity: Difference between revisions

Revision as of 07:17, 20 February 2018

Revision as of 16:19, 25 March 2020

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{{findsourcesnotice|sample complexity|"machine learning"}}

== Some keypoints for updating the article ==

* Metric Learning Sample Complexity [3]

* "low Sample Complexity" is more efficient [1]

* Model based Reinforcement learning has a lower sample complexity [2]

* sample complexity of Monte-Carlo Tree Search [4]

; Literature

* [1] Fidelman, Peggy, and Peter Stone. "The chin pinch: A case study in skill learning on a legged robot." Robot Soccer World Cup. Springer, Berlin, Heidelberg, 2006.

* [2] Kurutach, Thanard, et al. "Model-ensemble trust-region policy optimization." arXiv preprint arXiv:1802.10592 (2018).

* [3] Verma, Nakul, and Kristin Branson. "Sample complexity of learning mahalanobis distance metrics." Advances in neural information processing systems. 2015.

* [4] Kaufmann, Emilie, and Wouter M. Koolen. "Monte-carlo tree search by best arm identification." Advances in Neural Information Processing Systems. 2017.

--[[User:ManuelRodriguez|ManuelRodriguez]] ([[User talk:ManuelRodriguez|talk]]) 16:19, 25 March 2020 (UTC)