5.1 few-shot设置 5.2 zero-shot设置 5.3 X-trend结构讨论 六、相关工作 七、结论和展望 参考文献: 本文介绍了一种名为Cross Attentive Time-Series Trend Network(X-Trend)的新型预测模型,用于系统性交易策略。该模型旨在解决传统预测模型难以快速适应金融市场条件变化的问题。X-Trend通过在包含金融时间序列市场环境...
Time-frequency miningFew-shot learningMultivariate time series forecasting aims to accurately predict future trends by capturing and analyzing various features of the time series. Adequate training data are crucial for ensuring the model's generalizability. However, obtaining a sufficient amount of high-...
Learning complex time series forecasting models usually requires a large amount of data, as each model is trained from scratch for each task/data set. Leveraging learning experience with similar datasets is a well-established technique for classification problems called few-shot classification. However,...
Few-shot learning (FSL) 在机器学习领域具有重大意义和挑战性,是否拥有从少量样本中学习和概括的能力,是将人工智能和人类智能进行区分的明显分界点,因为人类可以仅通过一个或几个示例就可以轻松地建立对新事物的认知,而机器学习算法通常需要成千上万个有监督样本来保证其泛化能力。原则上我们将FSL方法分为基于生成模...
To address this issue, we introduce MetaTrans-FSTSF, a pioneering meta-learning framework that redefines few-shot time series forecasting. By innovatively integrating MAML and Transformer architectures, our framework provides a specialized solution tailored for the unique challenges of flood prediction, ...
定义:Few-shot learning是指,给定一个有特定于任务T的包含少量可用的有监督信息的数据集D_{T}和与T不相关的辅助数据集D_{A},小样样本学习的目标是为任务T构建函数f,该任务的完成利用了D_{T}中很少的监督信息和D_{A}中的知识,完成将输入映射到目标的任务。
time-serieseegecgforecastingclassificationimputationmulti-taskzero-shotanomaly-detectionfew-shotunified-modelprompt-tuningfoundation-models UpdatedSep 26, 2024 Python Tools for generating mini-ImageNet dataset and processing batches datasetimagenetone-shot-learningmeta-learningminiimagenetfew-shotfew-shot-learning...
We introduceEuroCropsML, an analysis-ready remote sensing dataset based on the open-sourceEuroCropscollection, formachine learning (ML)benchmarking of time series crop type classification in Europe. It is the first time-resolved remote sensing dataset designed to benchmark transnational few-shot crop...
FewShot Learning: 新一代机器学习技术的前沿 1. 背景介绍 在传统的机器学习和深度学习模型中,训练一个高性能的模型通常需要大量的标注数据。然而,在许多实际应用场景中,获取大量标注数据既昂贵又耗时。为了应对这一挑战,FewShot Learning(少样本学习)技术应运而生。FewShot Learning 旨在通过极少量的样本数据进行模型...
Few-Shot Prompting ist eine Technik, bei der ein KI-Modell einige Beispiele für eine Aufgabe erhält, aus denen es lernen kann, bevor es eine Antwort generiert, und diese Beispiele nutzt, um seine Leistung bei ähnlichen Aufgaben zu verbessern. ...