Overcoming Negative Transfer A Survey

Transfer learning aims to help the target task with little or no training data by leveraging knowledge from one or multi-related auxiliary tasks . Negative transfer is a long-standing problem in transfer learning literature, which has been well recognized within the transfer learning community… How to overcome negative transfer has been studied for a long time and has raised increasing attention in recent years . This survey attempts to analyze the factors related to negative transfer and summarizes theories and advances of overcoming negative transfer from four crucial aspects: source data quality, target data quality,. domain divergence and generic algorithms . It provides researchers a framework for better understanding and identifying the research status, fundamental questions, open challenges and future directions of the field. The survey provides researchers provides researchers with a framework to better understand and identify the research of the study. The study also provides some general guidelines on how to detect and overcome negative┬ádiscussions, including the negative transfer detection, datasets, baselines,

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Keywords : transfer - negative - learning - data - researchers -

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