Few-shot learning aims to learn from a few labeled examples. However, the limited training samples and weakly distinguishable embedding vectors in a metric space often lead to unsatisfactory test results and di
小样本学习(Few-shot learning)的目标是通过从基础知识中学习,最终识别具有有限支持样本的新查询。小样本学习假设基础知识和新查询样本在相同的领域中分布,虽然最近在这个设定下取得了一些进展,但对于实际应用来说这通常是不可行的。针对这个问题,本文提出解决跨领域小样本学习问题的方法,其中在目标领域中只有极少量的样...
Task-aware Adaptive Learning for Cross-domain Few-shot Learning Yurong Guo1, Ruoyi Du1, Yuan Dong1, Timothy Hospedales2, Yi-Zhe Song3, Zhanyu Ma1* 1Beijing University of Posts and Telecommunications, China 2University of Edinburgh, UK 3University of Surrey, UK ...
论文阅读笔记:Few-shot Classification via Adaptive Attention总的来说,现阶段大多数小样本学习都是基于metric learning或者meta learning。本文提出一种meta learning的方法,将注意力应用到小样本的场景。另…
论文阅读笔记《MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification》,程序员大本营,技术文章内容聚合第一站。
For popular few-shot learning benchmark tasks, we empirically show thatGAP outperforms the state-of-the-art MAML family and PGD-MAML family. Requirements This codes requires the following Python 3.6 or above PyTorch 1.8 or above Torchvision 0.5 or above ...
Ye, H.-J., Hu, H., Zhan, D.-C., Sha, F.: Few-shot learning via embedding adaptation with set-to-set functions. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 8808–8817 (2020) Ma, R., Fang, P., Avraham, G., Zuo, Y., Zhu, T...
Few-shot cross-domain fault diagnosis of bearing driven by task-supervised ANIL. IEEE Internet of Things Journal, 2024, 11(13): 22892–22902 Article MATH Google Scholar Lei Y G, Yang B, Jiang X W, Jia F, Li N P, Nandi A K. Applications of machine learning to machine fault ...
Paper tables with annotated results for Adaptive Weighted Co-Learning for Cross-Domain Few-Shot Learning
cross-domain few-shot learningFew-Shot Image Classification 773 Paper Code Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation 2 code implementations•28 Feb 2024 The meta-templates for a dataset produce training examples where the input is the unannotated text and the tas...