Reptile
reptile-bee13233·2 events·first seen 28d agoAliases: Reptile
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Reptile: A Scalable Meta-Learning Algorithm from OpenAI
OpenAI introduced Reptile, a meta-learning algorithm that works by repeatedly sampling tasks, running stochastic gradient descent, and updating initial parameters toward the task-specific learned parameters. It is mathematically related to first-order MAML but requires only black-box access to standard optimizers like SGD or Adam. The algorithm is positioned as computationally efficient and comparably performant to MAML-based approaches.
On First-Order Meta-Learning Algorithms
OpenAI published research on first-order meta-learning algorithms, presenting simplified variants of MAML (Model-Agnostic Meta-Learning) that omit second-order derivatives while retaining competitive performance. The work demonstrates that first-order approximations are surprisingly effective for few-shot learning tasks. This contributed to the broader understanding of gradient-based meta-learning efficiency and scalability.