Meta-Learning in Dialog Generation

Author(s): Edward Ma

Originally published on Towards AI.

Learning to learn

Unlike a well-known dataset, our real life problem domain always only have small labeled dataset while we may not able to train a good model under this scenario. Data augmentation is one of the way to generate syntactic data while meta-learning is another way to tackle this problem.

In this series of stories, we will go through different meta-learning approaches. One of the motivation for this task is that even children can recognize a object by giving just one example. Model does not learn to classify specific category but learning pattern to distinguish inputs. This series of meta-learning will cover Zero… Read the full blog for free on Medium.

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Published via Towards AI