Matrix Profile IV: Using Weakly Labeled Time Series to Predict Outcomes
Summary: Matrix Profile IV introduces SDTS, a domain-agnostic, parameter-free method for learning from weakly labeled time series with variable-length patterns. Rivals expert-tuned domain-specific methods in neuroscience and entomology. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,276 | Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series | 2020 | VLDB | 9.1261944e-05 |
| 5,999 | Time Series Data Mining: A Unifying View | 2023 | VLDB | 5.2415551e-05 |
| 10,561 | TELESAFE: Detecting Private/Work Boundary Crossings in Energy Consumption Trails in Telework | 2025 | VLDB | 4.1945683e-05 |
| 11,144 | Weakly Guided Adaptation for Robust Time Series Forecasting | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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