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Meta-learning the learning trends shared across tasks
Meta-learning stands for'learning to learn'such that generalization to new tasks is achieved.
Among these methods, Gradient-based meta-learning algorithms are a specific sub-class …
Among these methods, Gradient-based meta-learning algorithms are a specific sub-class …
Meta-learning with adjoint methods
Abstract Model Agnostic Meta-Learning (MAML) is widely used to find a good initialization
for a family of tasks. Despite its success, a critical challenge in MAML is to calculate the …
for a family of tasks. Despite its success, a critical challenge in MAML is to calculate the …
[PDF][PDF] Meta-Learning with Adjoint Methods
Abstract Model Agnostic Meta Learning (MAML) is widely used to find a good initialization
for a family of tasks. Despite its success, a critical challenge in MAML is to calculate the …
for a family of tasks. Despite its success, a critical challenge in MAML is to calculate the …
A Markov decision process approach to active meta learning
In supervised learning, we fit a single statistical model to a given data set, assuming that the
data is associated with a singular task, which yields well-tuned models for specific use, but …
data is associated with a singular task, which yields well-tuned models for specific use, but …