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transferability estimation

topic1 events
papersTODAY 04:00 UTC

Shapelet-Based Distance Measure Aims to Improve Multi-Source Transfer Learning for Time Series

A new arXiv preprint proposes selecting source datasets for time series classification by measuring similarity through shapelets, the discriminative subsequences that characterize time series patterns. The authors argue that transfer learning helps overcome limited labeled data in deep learning, but its usefulness hinges on picking appropriate source datasets. Their method is presented as an alternative to conventional transferability estimation, which the paper describes as computationally expensive.

transfer-learning/time-series/arxiv/research