DISC: Domain-Integrated Similarity Cost for Time-Series Dataset
Domain-Integrated Similarity Cost (DISC), a learnable aggregation framework that uses calibration transfer observations to select, weight, and combine similarity metrics for different downstream tasks, is proposed and shows that time-series dataset similarity is task-dependent and that learned metric integration provid...