proxy-label learning
Proxy-label learning is a machine learning approach where an auxiliary task, known as the proxy task, is used to learn a predictive model for a main task, which is difficult to directly learn due to the lack of labeled data. The proxy task is chosen to have a clear correlation with the main task, allowing the model to indirectly learn useful representations and improve performance on the main task.
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