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Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks.
Evolutionary principles in self-referential learning, or on learning how to learn: the meta-meta-… hook
Jürgen Schmidhuber · 1987
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Gradient-based optimization of hyperparameters
Y. Bengio · 2000
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Learning to learn using gradient descent
Sepp Hochreiter, A Steven Younger, and Peter R Conwell · 2001
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One shot learning of simple visual concepts
Brenden Lake, Ruslan Salakhutdinov, Jason Gross, and Joshua Tenenbaum · 2011
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Practical Bayesian optimization of machine learning algorithms
J. Snoek, H. Larochelle, and R. P. Adams · 2012
Earlier work this paper cites.
Learning to learn
Sebastian Thrun and Lorien Pratt · 2012
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Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
J. Bergstra, D. Yamins, and D. D. Cox · 2013
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An evaluation of sequential model-based optimization for expensive blackbox functions
F. Hutter, H. Hoos, and K. Leyton-Brown · 2013
Cited alongside, same era.
Human-level concept learning through probabilistic program induction
Brenden M Lake, Ruslan Salakhutdinov, and Joshua B Tenenbaum · 2015
Cited alongside, same era.
Gradient-based hyperparameter optimization through reversible learning
D. Maclaurin, D. K. Duvenaud, and R. P. Adams · 2015
Cited alongside, same era.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Tim Lillicrap, koray kavukcuoglu, and Daan Wierstra · 2016
Cited alongside, same era.
Meta-sgd: Learning to learn quickly for few shot learning
Zhenguo Li, Fengwei Zhou, Fei Chen, and Hang Li · 2017
Later among the works it cites.
Optimization as a model for few-shot learning
Sachin Ravi and Hugo Larochelle · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
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Online learning rate adaptation with hypergradient descent
Atılım Güneş Baydin, Robert Cornish, David Martínez Rubio, Mark Schmidt, and Frank Wood · 2018
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Meta learning deep visual words for fast video object segmentation
Harkirat Singh Behl, Mohammad Najafi, and Philip H. S. Torr · 2018
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How to train your MAML
Antreas Antoniou, Harrison Edwards, and Amos Storkey · 2019
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Cited alongside, same era.