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--- ml:metalearning [2021/02/18 15:06] – jmflanig
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-====== MetaLearning ======
-===== Deep Learning Papers =====
-  * [[https://jlab.soe.ucsc.edu/nlp-wiki/lib/exe/fetch.php?media=papers:learning_to_learn_using_gradient_descent.pdf|Learning to Learn Using Gradient Descent]]
-  * [[https://arxiv.org/pdf/1606.04474.pdf|Andrychowicz et al 2016 - Learning to Learn by Gradient Descent by Gradient Eescent]]
-  * [[http://proceedings.mlr.press/v70/chen17e/chen17e.pdf|Chen 2017 - Learning to Learn without Gradient Descent by Gradient Descent]] Learns a black-box optimizer (gradient-free optimizer).  Can be applied to hyperparameter tuning.
-  * [[https://arxiv.org/pdf/2012.14905.pdf|Kirsch & Schmidhuber 2021 - Meta Learning Backpropagation And Improving It]]
-===== Non-Deep Learning Papers =====
-  * **[[https://arxiv.org/pdf/2003.03384.pdf|Real et al 2020 - AutoML-Zero: Evolving Machine Learning Algorithms From Scratch]]**
-  * [[https://arxiv.org/pdf/2101.08809.pdf|Peng et al 2021 - PyGlove: Symbolic Programming for Automated Machine Learning]]
-===== Related Pages =====
-  * [[Neural Architecture Search]]