DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend ForecastingAug 1, 2023·Lifan Zhao,Shuming Kong,Yanyan Shen· 0 min read PDF Cite Code Project Slides Video DOITypeConference paperPublicationProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'23)Last updated on Aug 1, 2023 AuthorsLifan ZhaoPhD candidate ← StockCL: Selective Contrastive Learning for Stock Trend Forecasting via Learnable Concepts Jan 1, 2024RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction Feb 1, 2023 →
