Talk:Sample complexity
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Some keypoints for updating the article
[edit ]- 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.
--ManuelRodriguez (talk) 16:19, 25 March 2020 (UTC) [reply ]
Sample efficiency in Reinforcement learning
[edit ]Not sure this is the same. It is discissed here as well: https://ai.stackexchange.com/questions/38775/do-the-terms-sample-complexity-and-sample-efficiency-mean-the-same-thing-in I would love to know more. Could somebody add information from a reputable source? Biggerj1 (talk) 19:13, 22 January 2024 (UTC) [reply ]