arXiv Machine Learning By Carlos H. Mendoza-Cardenas, Rogers F. Silva, Austin J. Brockmeier

QSMP: finding representative time series subsequences through Quick Shift+Matrix Profile

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arXiv:2608. 15492v1 Announce Type: new Abstract: Finding representative waveforms in long time series has scientific and practical value in many domains, as it enables summarization and visualization of large time series datasets, and downstream tasks like classification and forecasting.

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arXiv Machine Learning
Jun 19

Spectral Retrieval-Augmented Time-Series Forecasting

arXiv:2606. 19412v1 Announce Type: new Abstract: Time series forecasting leverages historical patterns to predict future values, but traditional methods face challenges when dealing with complex, non-stationary patterns that are difficult to memorize during training.

By Huu Hiep Nguyen, Minh Hoang Nguyen, Dung Nguyen, Hung Le