Meta-Learning a Dynamical Language ModelDownload PDF

12 Feb 2018 (modified: 05 May 2023)ICLR 2018 Workshop SubmissionReaders: Everyone
Abstract: We consider the task of word-level language modeling and study the possibility of combining hidden-states-based short-term representations with medium-term representations encoded in dynamical weights of a language model. Our work extends recent experiments on language models with dynamically evolving weights by casting the language modeling problem into an online learning-to-learn framework in which a meta-learner is trained by gradient-descent to continuously update a language model weights.
Keywords: language models, hierarchical representations, meta-learning, nonstationarity, catastrophic forgetting, recurrent neural network
TL;DR: Language modeling with dynamical weights as an instance of continuous meta-learning
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