Tag: Meta-Learning


Few-Shot Text Classification With Distributional Signatures

本文提出了一种少样本下的元学习方法,用于文本分类,在多个数据集上取得较好效果。 paper: https://drive.google.com/open?id=19HtiZOH1jKWtEu_pq38wVYtYOwNIvPiPcode: https://github.com/YujiaBao/Distributional-Signaturessource: Work in Progress for ICLR2020


Meta-Learning Learning to Learn

Meta-learning, also known as “learning to learn”, intends to design models that can learn new skills or adapt to new environments rapidly with a few training examples. There are three common approaches: 1) learn an efficient distance metric (metric-based); 2) use (recurrent) network with external or internal memory (model-based); 3) optimize the model parameters explicitly for fast learning (optimization-based).