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YADING: Fast Clustering of Large-Scale Time Series Data

Summary: YADING—end-to-end time-series clustering via sampling: cluster a subset and assign the rest, with theory-backed bounds for distributional consistency and robustness to phase perturbation and noise using L1 and multi-density. On 100k×1k data, it is ~40× faster than DENCLUE 2.0 and ~1k× faster than DBSCAN/CLARANS; demonstrated in Microsoft product analyses. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11159
Venue
VLDB
Year
2015
Pagerank
5.8956566e-05
Overall Rank
4,823 | 66.45%
DOI
-

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