Метаобучение на основе оптимизации

method ID: optimizationbasedmetalearning

Related Papers

Diverse Few-Shot Text Classification with Multiple Metrics

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractWe study few-shot learning in natural language domains. Compared to many existing works that apply either metric-based or optimization-based meta-learning to image domain with low inter-task variance, we consider a …...

20925

Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractTask-oriented semantic parsing is a critical component of virtual assistants, which is responsible for understanding the user’s intents (set reminder, play music, etc.). Recent advances in deep learning have enabled …...

30254

Adaptive Meta-learner via Gradient Similarity for Few-shot Text Classification

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractFew-shot text classification aims to classify the text under the few-shot scenario. Most of the previous methods adopt optimization-based meta learning to obtain task distribution. However, due to the neglect …...

4792

Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractBuilding models of natural language processing (NLP) is challenging in low-resource scenarios where limited data are available. Optimization-based meta-learning algorithms achieve promising results in low-resource scenarios by adapting a well-generalized …...

39333