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Chapter and Conference Paper
Adaptive Knowledge Sharing in Multi-Task Learning: Insights from Electricity Data Analysis
In time-series machine learning, the challenge of obtaining labeled data has spurred interest in using unlabeled data for model training. Current research primarily focuses on deep multi-task learning, emphasi...
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Chapter and Conference Paper
Modeling Transitions of Inter-segment Patterns for Time Series Representation
Against the backdrop of technological advancements, we are now equipped to collect and analyze time series data in unparalleled ways, offering significant value across various fields. However, traditional time...
